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Active In SP

Posts: 53
Joined: Nov 2010
17-11-2010, 11:27 AM

Submitted by
Bibin Mohanan
Roll no. 21
2007-11 batch



What is Radar?
Principle of operation
Radar limiting factors
Radar signal processing
Applications of Radar signal processing
Driver Assistance System
Design of FPGA based Radar signal processing system.
Safety and comfort applications are addressed using Driver Assistance systems.
Radar based DA systems are already available for some luxury cars and heavy transport vehicles.
DA systems can handle several tasks such as collision avoidance, lane change assistance, parking assistance etc.
DA multi-sensor systems require complex algorithms and advanced digital hardwares.
What is Radar?
The term Radar was coined in 1941.
Radar: Radio detection and ranging.
It is an electromagnetic sensor for the detection and location of reflecting objects.
Radar can measure range, angular direction, trajectory and angular velocity of targets.
Radar might be small enough to hold in the palm of one hand or large enough to occupy the space of many football fields.
Radar targets might be aircrafts , ships, missiles, land features, underground features, spacecrafts, planets etc.

Principle of operation
A radio transmitter emits an electromagnetic pulse and waits for the echo.
A common waveform radiated by a radar is a series of relatively narrow, rectangular like pulses.
The echo signal (reflected signal) is received and processed by the receiver part.
Each reflection scales the amplitude of the wave down by a factor.
Echoes from targets consist of scaled and shifted (or delayed) versions of the originally transmitted pulse.

Radar block diagram

Radar Limiting factors
Beam path and range : Radar beam follows a curved path in the atmosphere due to the variations of the refractive index of the air.
Noise: Internal & external sources of noise.
Interference : Unwanted signals affect the operation. Natural& Manmade.
Jamming: radio frequency signals originating from sources outside the radar, transmitting in the radar's frequency and thereby masking targets of interest.
Clutter: radio frequency (RF) echoes returned from targets which are uninteresting to the radar operators.
Radar Signal processing
DSP techniques are used to extract informations about the target.
Radar signal processor separates the desired signal from unwanted signals.
At the transmitter end, it generates and shapes the transmission pulses, controls the antenna beam pattern.
At the receiver, DSP performs many complex tasks, including STAP (space time adaptive processing) - the removal of clutter, and beam forming .
Radar signal processing techniques: Moving target indication, Pulse Doppler, Moving target detection, Constant false alarm rate etc.

Tasks of Radar signal processor

Decision making.
Combining information.
Forming tracks.
Ground clutter mapping.
Resolving ambiguities in range measurements.
Countering interference.
Distance measurement.
Speed measurement.
Frequency modulation.
Applications of Radar signal processing
Weather forecasting
Driver assistance systems
Remote Sensing

Driver assistance systems

Night vision.
Adaptive Cruise Control.
Collision warning.
Collision avoidance.
Driver impairment monitoring.
Cooperative infrastructure.
Automated Driving.

Radar based Driver Assistance Systems
This can handle complex features such as collision avoidance, prediction of dangerous situation, lane change assistance, parking assistance etc.
Consist of the use of Frequency Modulated Continuous Wave (FMCW) modulation.
A flexible FPGA based architecture is used for the implementation of the underlined digital signal processing.
Design steps
B. System requirements
C. Waveform and underlined Algorithm

Timing Diagram
There’s a lot going on! …. A diverse array of activity for all vehicle types.
Look for increasingly intelligent vehicles to move most rapidly into commercial vehicle markets -- where the intelligence enhances the bottom line.
Look for consumers to become increasingly comfortable with driver aids and demand more relief from the tedium of driving ….and look for the technology to deliver.
Discussed prototype is flexible and enables rapid integration of new eventual features.

Jean Saad , Amer Baghdadi, Frantz Bodereau, “FPGA based Radar signal processing for Automotive Driver Assistance System”, IEEE/IFIP International Symposium on Rapid System Prototyping,vol.40,no.2, pp.196-199, November 2009.
Stove, A.G., “Linear FMCW radar techniques”, IEEE transactions on Radar and Signal Processing ,vol.139, no.5, pp.343-350, Oct 2007.
Basten, M. J., “Low Cost Implementation of an ACC Automotive Radar”, Institution of Engineering and Technology Seminar on MM-Wave Products and Technologies, vol.49, no.6, pp.1-6, Sept 2006.

Active In SP

Posts: 53
Joined: Nov 2010
17-11-2010, 11:51 AM

Submitted by
Bibin Mohanan
Roll no. 21

Driver assistance systems use a combination of warnings and some degree of active
intervention to help steer the driver away from trouble. Although the accent is on giving
assistance to the driver rather than take control away, motorists are still wary about cars that
supposedly drive themselves. While active intervention clearly holds many possibilities, it is
also fraught with difficulty. A number of manufacturers are pursuing the aim of reducing the
frequency and severity of accidents by developing active and passive driving assistance
systems. Driver assistance systems aim to make the vehicle capable of perceiving its
surroundings, interpret them, identify critical situations, and assist the driver in performing
driving maneuvers. The object is, at best, to prevent accidents completely and, at worst, to
minimize the consequences of an accident for those concerned.. Consequently, these systems
are increasingly being incorporated in cars across the board, from luxury vehicles to small
city cars. Indeed, many of these systems are being fitted as standard equipment.
Driver assistance systems have become more popular with the introduction of 24GHz
radar systems for passenger cars. The car manufactures are now focusing their interest on
fusion-based multi-sensor systems, enabling the car to monitor the whole environment. One
of the requirements resulting from this system set-up is a new distribution of signal
processing blocks between sensor(s) and a central Engine Control Unit(ECU). As this fusion-
ECU becomes responsible for data validation, object recognition, object tracing and
communication with the car network, the sensor itself becomes a simple data acquisition unit.
Ideally it would transfer all data to the central ECU for processing. Assuming a typical cycle
time of 30-40ms this could result in data rates up to 2.9Mbit/s per sensor. This bandwidth
isn’t available with today’s car networks; therefore some data pre-processing and data
reduction has to be performed in the sensor. One approach is to implement the required signal
processing in an FPGA. With their internal multipliers and RAM blocks, they offer an
unbeatable DSP performance at a moderate frequency. Their architecture is suitable for the
whole algorithm including offset correction, FFT and digital beam forming. Even tasks like
threshold calculation and spectral peak detection can be performed within the FPGA.

Radar is an object-detection system that uses electromagnetic waves - specifically
radio waves - to identify the range, altitude, direction, or speed of both moving and fixed
objects such as aircraft, ships, spacecraft, mountain ranges, radio and TV towers, guided
missiles, motor vehicles, weather formations, and terrain. The radar dish, or antenna,
transmits pulses of radio waves or microwaves which bounce off any object in their path. The
object returns a tiny part of the wave's energy to a dish or antenna which is usually located at
the same site as the transmitter.
The term RADAR was coined in 1940 by electronics engineers working for the U.S.
Navy as an acronym for Radio Detection And Ranging. The uses of radar include air traffic
control, radar astronomy, air-defense systems, antimissile systems; nautical radars to locate
landmarks and other ships; aircraft anticollision systems, ocean-surveillance systems, outerspace
surveillance and rendezvous systems; meteorological precipitations, radar altimeters,
earth-skimming flight-control systems, guided-missile target-locating systems, and groundpenetrating
RADAR transmits radio signals at distant objects and analyzes the reflections. Data
gathered can include the position and movement of the object, also radar can identify the
object through its "signature" - the distinct reflection it generates. There are many forms of
RADAR - such as continuous, CW, Doppler, ground penetrating or synthetic aperture; and
they're used in many applications, from air traffic control to weather prediction. In the
modern Radar systems digital signal processing (DSP) is used extensively. At the transmitter
end, it generates and shapes the transmission pulses, controls the antenna beam pattern while
at the receiver, DSP performs many complex tasks, including STAP (space time adaptive
processing) - the removal of clutter, and beamforming (electronic guidance of direction).
The front end of the receiver for RADAR is still often analog due the high frequencies
Involved. With fast ADC convertors- often multiple channel, complex IF signals are
digitized. However, digital technology is coming closer to the antenna. We may also require
fast digital interfaces to detect antenna position, or control other hardware.

A Radar system has a transmitter that emits radio waves called radar
signals in predetermined directions. When these come into contact with an object they are
usually reflected and/or scattered in many directions. Radar signals are reflected especially
well by materials of considerable electrical conductivity - especially by most metals, by
seawater, by wet land, and by wetlands. Some of these make the use of radar altimeters
possible. The radar signals that are reflected back towards the transmitter are the desirable
ones that make radar work. If the object is moving either closer or farther away, there is a
slight change in the thus frequency of the radio waves, due to the Doppler effect. Radar
receivers are usually, but not always, in the same location as the transmitter. Although the
reflected radar signals captured by the receiving antenna is usually very weak, these signal
can be strengthened by the electronic amplifiers that all radar sets contain. More sophisticated
methods of signal processing are also nearly always used in order to recover useful radar
The small absorbtion of radio waves by the medium through which it passes is what
enables radar sets to detect objects at relatively-long ranges - ranges at which other
electromagnetic wavelengths, such visible light, infrared light, and ultraviolet light are too
strongly attenuated. In particular, there are weather conditions under which radar works well
regardless of the weather. Such things as fog, clouds, rain, falling snow, and sleet that block
visible light are usually transparent to radio waves. Certain, special values of radio
frequencies are absorbed or scattered by water vapor, raindrops, or atmospheric gases
(especilly oxygen) are avoided in designing radars except when detection of these are
intented. Finally, radar relies on its own transmissions, rather than light from the Sun or the
Moon, or from electromagnetic waves emitted by the objects themselves, such as infrared
wavelengths (heat). This process of directing artificial radio waves towards objects is called
illumination, regardless of the fact that radio waves are completely invisible to the human eye
or cameras.

Fig 1: Radar block Diagram
2.2.1. Antenna and scan pattern generator:
This determines the shape and direction of TX/RX beam. The antenna can be either a
mechanically rotating reflector or a phased array electronically steered in azimuth and
elevation. The antenna allows transmitted energy to be propagates into space and then
collects the echo energy on receive. It is almost always a directive antenna, one that directs
the radiated energy into narrow beam to concentrate the power as well as to allow the
determination of direction to the target. An Antenna that produces a narrow directive beam
on transit usually has a large area on receive to allow the collection of weak echo signals
from the target. The antenna not only concentrate energy on transmit and collect the echo
energy on receive, but it also act as a spatial filter to provide angle resolution and other
It is generally a tube generating a coherent pulse train with high peak power and
possibly a wide band; alternatively, mini TWT or solid state amplifiers can be used in active
phased-array radar.

2.2.3.Waveform generator:
It tailors the waveform to the environment and to the particular operating mode
actually used. The waveforms can be wide pulse with frequency or phase code modulation
for improved range resolution and clutter discrimination.
This is an RF switch which conveys all the energy from the transmitter to the antenna
in the transmitting phase while all the energy gathered by the antenna in the receiving phase
is sent directly to the receiver chain. The rotary joint, allows the electric connection of the
antenna to the remaining part of the radar notwithstanding the mechanical rotation of the
antenna. Rotary joint with low loss and optical fibres for the transportation of signals are
today available.
It provides frequency conversion, interference rejection and low noise amplification.
The noise reduction is an important consideration in radar receiver design and is
accomplished by the matched filter technique which maximises the SNR at the output. Signal
down conversion in frequency is done in a number of steps up to base band where the signal
is transformed in digital format via analogue-to-digital conversion (ADC) devices. Modern
radar performs the ADC directly at intermediate frequency (IF); the advantage is to eliminate
the unbalance between the I (in phase) and quadrature (Q) channels with corresponding
advantages in terms of coherent rejection of clutter & jammer and integration of target echoes
The trend today is towards a so called digital radar where the ADC is done very close to the
2.2.6.Signal processor:
This determines the presence or absence of targets while rejecting unwanted signals
due to ground clutter, sea clutter, weather, radio-frequency interference, noise sources and
intentional jammers. It is performed by coherent and/or not-coherent processing of time
samples of received signals. The coherent processing acts on the I and Q components of
signal collected during the time on target, while the non-coherent processing occurs after
phase information is suppressed in the envelope detector. Detection is accomplished by
comparing the processed video output with a threshold value, the crossing of the threshold
being declared detection.

The signal processor is implemented in real time special-processor hardware; more
recently due to the extraordinary advances of the digital technology the processor makes
extensive use of COTS (Commercial Off The Shelf) devices. Basic operations routinely
implemented are: pulse compression, moving target indicator (MTI), pulse Doppler
processing, moving target detector (MTD), CFAR .Also some modern phased-array radar
have implemented in their signal processors the adaptive spatial filtering of jammers NCTR
is another function that may be implemented in modern radar.
2.2.7.Data extractor& Processor:
This provides the target measurements in range, angles (azimuth, elevation) (via
moving window or monopulse), radial speed and possibly target signature for NCTR. In
general, target may cause several detections in adjacent cells in range, Doppler and angles;
the centroid (referred to as “plot” in the sequel) of the corresponding pattern of detections
gives an estimate of the target measurement. The target extractor was Implemented in a
dedicated microcomputer; today COTS technology is used also here.It is essentially where
the tracking filtering is implemented.
The output is generally a display to visualise the information contained in the radar
echo signal in a form suitable for operator interpretation and action. There could be a link to
convey data in a centre or in a computer for further processing. The visualised information on
the display is called synthetic video. The plan position indicator (PPI), the usual display
employed in radar, indicates the range and azimuth of a detected target. A modern radar
display includes alphanumeric characters and symbols for directly conveying additional
information; this is useful when target identity and altitude are to be displayed. Also the track
is displayed with arrows and symbols.
This decodes commands from the operator and sets up the operation modes, the
appropriate system timing and the signal generator together with the processing functions on
the received signals according to range, azimuth and elevation sectors. The controller also
analyses signals for fault detection. It normally comprises a set of software programs
implemented on a digital computer; used technologies are multiprocessor architectures based
on COTS (Power PC and the like); programming languages can be Ada and C; real time
operative system may be Lynx-OS or similar.

The various factors which limits the operation of Radar are
2.3.1. Beam path and range:
The radar beam would follow a linear path in vacuum but it really follows a somewhat
curved path in the atmosphere due to the variation of the refractive index of air. Even when
the beam is emitted parallel to the ground, it will raise above it as the Earth curvature sink
below the horizon. Furthermore, the signal is attenuated by the medium it crosses and the
beam disperse as its not a perfect pencil shape. The maximum range of a conventional radar
at a certain height above ground is thus limited by the maximum non-ambiguous range
determined by the Pulse repetition frequency (PRF), the two way intensity of the returned
signal according to the radar equation and the Earth curvature.
Signal noise is an internal source of random variations in the signal, which is generated
by all electronic components. Noise typically appears as random variations superimposed on
the desired echo signal received in the radar receiver. The lower the power of the desired
signal, the more difficult it is to discern it from the noise (similar to trying to hear a whisper
while standing near a busy road). Noise figure is a measure of the noise produced by a
receiver compared to an ideal receiver, and this needs to be minimized. Noise is also
generated by external sources, most importantly the natural thermal radiation of the
background scene surrounding the target of interest. In modern radar systems, due to the high
performance of their receivers, the internal noises is typically about equal to or lower than the
external scene noise. An exception is if the radar is aimed upwards at clear sky, where the
scene is so "cold" that it generates very little thermal noise.

Radar systems must overcome unwanted signals in order to focus only on the actual
targets of interest. These unwanted signals may originate from internal and external sources,
both passive and active. The ability of the radar system to overcome these unwanted signals
defines its signal-to-noise ratio (SNR). SNR is defined as the ratio of a signal power to the
noise power within the desired signal. In less technical terms, SNR compares the level of a
desired signal (such as targets) to the level of background noise.
Clutter refers to radio frequency (RF) echoes returned from targets which are
uninteresting to the radar operators. Such targets include natural objects such as ground, sea,
precipitation (such as rain, snow or hail), sand storms, animals (especially birds), atmospheric
turbulence, and other atmospheric effects, such as ionosphere reflections, meteor trails, and
three body scatter spike. Clutter may also be returned from man-made objects such as
buildings and, intentionally, by radar countermeasures such as chaff. Some clutter may also
be caused by a long radar waveguide between the radar transceiver and the antenna. In a
typical plan position indicator (PPI) radar with a rotating antenna, this will usually be seen as
a "sun" or "sunburst" in the centre of the display as the receiver responds to echoes from dust
particles and misguided RF in the waveguide. Adjusting the timing between when the
transmitter sends a pulse and when the receiver stage is enabled will generally reduce the
sunburst without affecting the accuracy of the range, since most sunburst is caused by a
diffused transmit pulse reflected before it leaves the antenna..
Radar jamming refers to radio frequency signals originating from sources outside the
radar, transmitting in the radar's frequency and thereby masking targets of interest. Jamming
may be intentional, as with an electronic warfare (EW) tactic, or unintentional, as with
friendly forces operating equipment that transmits using the same frequency range. Jamming
is considered an active interference source, since it is initiated by elements outside the radar
and in general unrelated to the radar signals.

Jamming is problematic to radar since the jamming signal only needs to travel one-way
(from the jammer to the radar receiver) whereas the radar echoes travel two-ways (radartarget-
radar) and are therefore significantly reduced in power by the time they return to the
radar receiver. Jammers therefore can be much less powerful than their jammed radars and
still effectively mask targets along the line of sight from the jammer to the radar (Mainlobe
Jamming). Jammers have an added effect of affecting radars along other lines of sight, due to
the radar receiver's sidelobes (Sidelobe Jamming)

Radar signal processing can be defined as the manipulation of the received signal,
represented in digital format, to extract the desired information whilst rejecting unwanted
signals. In particular, a surveillance radar takes a decision about the presence or absence of
targets whilst cancelling radar echoes caused by ground clutter, radio frequency interference
and noise source. An airborne radar accomplishes the same job in spite of the strong clutter
return and its Doppler spread caused by the platform motion. A tracking radar, in addition to
detection, is concerned with an accurate estimation of the target kinematics parameters (resort
is made to maximum likelihood estimation procedure and its sub-optimum implementations).
The list could be extended to other radar systems as the low probability of intercept, the
synthetic aperture radar, the space-based radar and the multistatic radar.
Whatever the radar system, the basic operations performed by the signal and data
processors are as follows: detection of presence of targets, if any; extraction of information
from the received waveform to determine a wealth of relevant parameters of the targets (such
as position, velocity, shape, and electromagnetic signature). The first step of the design can
be recognised in the formulation of mathematical models more adherent to the real
environment in which the radar operates. Several major areas of research and development
can be singled out in connection with radar detection: theory of optimum detection, adaptive
detection theory, detection of signals having non-Gaussian probability density function (pdf),
multidimensional processing and super resolution algorithms .Some techniques have been
successfully implemented in real radar systems.

3.1.1. Decision making:
After a signal has been transmitted, the receiver starts receiving return signals, with
those originating from near objects arriving first because time of arrival translates into target
range. The signal processor places a raster of range bins over the whole period of time, and
now it has to make a decision for each of the range bins as to whether it contains an object or
not. This decision-making is severely hampered by noise. Atmospheric noise enters into the
system through the antenna, and all the electronics in the radar's signal path produces noise
too. Even if atmospheric attenuation can be neglected, the return from a distant object is
incredibly weak. Target returns often are no stronger than twice the average noise level,
sometimes even buried under it. It is quite difficult to define a threshold for the decision
whether a given peak is noise or a real target. If the threshold is too high then existing targets
are suppressed, that is, the probability of detection (PD) will drop. If the threshold is too low
then noise peaks will be reported as targets, that is, the probability of false alarms (PFA) will
rise. A common compromise is to have some 90% probability of detection and a false alarm
rate of 10^-6.
3.1.2.Combining information:
Secondary surveillance radars like those located on airports can ask an aircraft's
transponder for information like height, flight number or fuel state. Pilots may also issue a
distress signal via the transponder. The ground radar's signal processor combines t his data
with its own measurements of range and angular direction and plots them all together on the
appropriate spot on the scope.
3.1.3.Forming tracks:
By correlating the data sets which were obtained in successive scan cycles, the radar
can calculate a flight vector which indicates an aircraft's speed and expected position for the
next scan period. Airport radars are capable of tracking hundreds of targets simultaneously,
and flight safety depends heavily on their reliability. Military tracking radars use this
information for gun laying or guiding missiles into some calculated collision point.

3.1.4.Resolving ambiguities in range:
Depending on the radar's pulse repetition frequency (PRF), the readings for range,
Doppler or even both are ambiguous. The signal processor is aware of this and selects a
different PRF when the object in question is measured again. With a suitable set of PRFs,
ambiguities can be eliminated and the true target position can be determined..
3.1.5.Ground Clutter Mapping:
Clutter is the collective term for all unwanted blips on a radar screen. Ground clutter
originates from buildings, cars, mountains etc, and a clutter map serves to raise the decision
threshold in areas where known clutter
sources are located.
3.1.6.Time and power management:
Within a window of some 60°x40°, phased array radars can instantly switch their beam
position to any position in azimuth and elevation. When the radar is tasked with surveying its
sector and tracking dozens of targets, there's a danger of either neglecting part of the search
sector or losing a target if the corresponding track record isn't updated in time. Time
management serves to maintain a priority queue of all the tasks and to produce a schedule for
the beam steering device. Power management is necessary if the transmitter circuitry runs the
danger of overheating. If there's no backup hardware then the only way of continuing regular
operation is to use less power when less power is required, say, for track confirmation.
3.1.7.Countering interference:
Interference can be a) natural, or b) man-made. Natural interference can be heavy rain
or hail storms, but also varied propagation conditions. Man-made interference, if created on
purpose, is also called jamming and is one of the means of electronic countermeasures.
The information provided by radar includes the bearing and range (and therefore
position) of the object from the radar scanner. It is thus used in many different fields where
the need for such positioning is crucial. The first use of radar was for military purposes; to
locate air, ground and sea targets. This has evolved in the civilian field into applications for
aircraft, ships and roads.
In aviation, aircraft are equipped with radar devices that warn of obstacles in or
approaching their path and give accurate altitude readings. They can land in fog at airports
equipped with radar-assisted ground-controlled approach (GCA) systems, in which the
plane's flight is observed on radar screens while operators radio landing directions to the
Marine radars are used to measure the bearing and distance of ships to prevent
collision with other ships, to navigate and to fix their position at sea when within range of
shore or other fixed references such as islands, buoys, and lightships. In port or in harbour,
Vessel traffic service radar systems are used to monitor and regulate ship movements in busy
waters. Police forces use radar guns to monitor vehicle speeds on the roads.
Radar has invaded many other fields. Meteorologists use radar to monitor
precipitation. It has become the primary tool for short-term weather forecasting and to watch
for severe weather such as thunderstorms, tornadoes, winter storms precipitation types, etc...
Geologists use specialised ground-penetrating radars to map the composition of the Earth
crust. The list is getting longer all the time.


Radar sensor based Driver Assistance Systems are already available for some luxury
cars and heavy transport vehicles. First radar systems generation supports limited
functionality like Adaptive Cruise Control (ACC), where the main tasks are to detect targets,
infer useful information, and adjust the speed of the vehicle accordingly. Today’s generation
is more sophisticated. It proposes to handle multiple complex features such as collision
avoidance, prediction of dangerous situations, lane change assistance, parking assistance, and
many others. It consists of the use of Frequency-Modulated Continuous Wave (FMCW)
modulation which allows managing complex detection scenarios.
Fig 2: System level architecture of DA radar-based system
4.1.1.Night vision:
An automotive night vision system is a system to increase a vehicle driver's perception
and seeing distance in darkness or poor weather beyond the reach of the vehicle's headlights.
They are currently offered as optional equipment on certain premium vehicles.
4.1.2.Adaptive Cruise Control:
These systems use either a radar or laser setup allowing the vehicle to slow when
approaching another vehicle and accelerate again to the preset speed when traffic allows.
ACC technology is widely regarded as a key component of any future generations of
intelligent cars. The system consist of a forward looking Radar which sees slower vehicles
ahead. Now the system automatically adjusts speed and maintains a selectable following
distance. The desired speed is resumed when the way ahead is clear. Some ACC systems use
digital maps to enhance operations.
4.1.3.Collision avoidance:
A collision avoidance system is a system of sensors that is placed within a car to warn
its driver of any dangers that may lie ahead on the road. Some of the dangers that these
sensors can pick up on include how close the car is to other cars surrounding it, how much its
speed needs to be reduced while going around a curve, and how close the car is to going off
the road. The system uses sensors that send and receive signals from things like other cars,
obstacles in the road, traffic lights, and even a central database are placed within the car and
tell it of any weather or traffic precautions. A situation that provides a good example of how
the system works is when a driver is about to change lanes, and there is a car in his blind spot.
The sensors will detect that car and inform the driver before he starts turning, preventing him
from potentially getting into a serious accident. Collision avoidance systems are especially
useful in bad weather conditions. The sensors in the car would be capable of detecting the
poor conditions and would inform the driver on how to drive in them.
4.1.4.Driver impairment monitoring:
This system examine ,is the driver is fit to drive? It monitor the driving performance
such as lane keeping, steering wheel monitoring and physiological factors like ocular
measures, head position monitoring etc.It is equipped with a proximity array sensor system.
4.1.5.Lane departure warning:
In road-transport terminology, a lane departure warning system is a mechanism
designed to warn a driver when the vehicle begins to move out of its lane (unless a turn signal
is on in that direction) on freeways and arterial roads. These systems are designed to
minimize accidents by addressing the main causes of collisions: driving error, distraction and
There are two main types of systems:
• Systems which warn the driver if the vehicle is leaving its lane. (visual, audible,
and/or vibration warnings)
• Systems which warn the driver and if no action is taken automatically take steps to
ensure the vehicle stays in its lane.
4.1.6.Automatic parking:
Automatic parking is an autonomous car maneuvering from a traffic lane into a
parking place to perform parallel parking, perpendicular or angle parking. The automatic
parking aims to enhance the comfort and safety of driving in constrained environments where
much attention and experience is required to steer the car. The parking maneuver is achieved
by means of coordinated control of the steering angle and speed which takes into account the
actual situation in the environment to ensure collision-free motion within the available space.
Radar and sonar applications are signal-processing intensive and heavily rely on the
efficient implementation of such digital signal-processing (DSP) algorithms as filtering,
transforms and modulation. In past systems, conventional digital signal processors were used
to perform many of these algorithms. However, field-programmable gate arrays (FPGAs)
deliver an order of magnitude higher performance than traditional DSPs. A key reason is that
an FPGA can side step the classic Von Neumann architecture's instruction — fetch,
load/store bottleneck — found in most DSPs. Another reason is the FPGA's lower power
As FPGAs increase in density and performance capability, more signal-processing
functions can be incorporated and migrated to the front end containing the exciter/receiver of
the radar (or sonar) system. This may include waveform generation, filtering, matrix-inverse
operations, and signal correlation.
Fitting multiple DSP functions into a single FPGA has many integration challenges,
but also offers significant advantages to the designer in performance and flexibility. The
primary reasons for integrating DSP functions into a single FPGA are system-level reductions
in size, weight and power. For example, eliminating the transfer pathways between separate
FPGAs and DSPs significantly reduces power consumption and, therefore, heat. This, in turn,
reduces the system-cooling burden of the design. Recent releases of design and place-androute
software, such as Altera's Quartus II design suite, have advanced power-awareness
features that significantly reduce dynamic power use of the FPGA. These options can be
important to the designer; the benchmark of device logic density among competitive FPGA
providers is beginning to give way to functionality-per-watt metrics, due to the sensitivity of
power and cooling requirements in emerging systems.
Performance is also a key driver as FPGA-pipelined signal processing has become
more reliable and faster than traditional processing technologies. In applications where
performance is the driving parameter, efficiency can be sacrificed for application speed,
where a memory-intensive, massively parallel floating-point math operation is desired.
Alternatively, highly iterative DSP calculations can be implemented for applications where
moderate performance is allowable, but where logic-element usage is limited. This leads to
the advantage of flexibility. The designer has the flexibility to decide between high-speed
performance and the number of logic elements in every DSP operation, whereas calculation
bandwidths and iterations would be more difficult and costly to modify in a dedicated DSP
device. In addition, consolidating DSP functions within an FPGA allows for post-design
system changes in the signal-processing architecture, whereas using separate DSPs locks the
designer into a fixed set of chip interfaces once the board is designed. FPGA designers can
alternately switch between 9-bit, 18-bit or 36-bit or 18-bit complex math functions without
changing the system hardware.
Additional flexibility can be designed into the system when the designer uses fastembedded
processors for the execution or routing of complex floating-point operations.
These functions are useful for radar applications.
Several DSP functions are needed for radar or sonar processing near the receiver
element. Each function should be closely examined to determine whether the application will
show substantial speed and performance improvements through implementation in an FPGA.
In some cases, these operations can be efficiently implemented using an FPGA embedded
processor, even for highly complex and adaptive operations.
When a radar or sonar application calls for these operations to be performed with
floating-point arithmetic, FPGAs have significant flexibility advantages if the design team
takes advantage of a strong architecture-based design approach. Large floating-point math
operations can be performed in standard logic cells (the least efficient option), in dedicated
reduced-instruction-set-computer (RISC) embedded processors (the most flexible option), or
in dedicated floating-point multiplier logic (the most efficient option).
FPGA providers and third-party developers offer efficient and accurate floating-point
operators, Fourier-transform tools and filter compilers to FPGA designers as intellectual
property (IP). Engineers should conduct their own research on the current availability of
advanced DSP functions, but a great deal of preliminary information can be obtained through
the technical representatives of programmable logic device (PLD) vendors.
The upconversion and downconversion of high-frequency signals are experiencing a
dual migration, into the digital domain, and into the same monolithic device (either the ASIC
or FPGA) that performs the baseband processing. This push toward more digital, softwareradio-
style signal-processing techniques provides significant advantages to the system in
signal accuracy and speed. The closer to the RF front end (or the acoustic transceiver front
end in sonar systems) that signals can be digitized, the fewer the analog-signal vulnerabilities
that are introduced to the system. This includes high-order mixing products, error-vectormagnitude
(EVM) impairments due to phase/magnitude imbalance, carrier feed-through,
harmonics, and sideband noise.
More important than signal integrity, however, is the design flexibility that the digital
domain allows the radar-system designer. Dynamic filtering and conditional signalprocessing
algorithms significantly improve performance, as well as reduce implementation
losses and the time required for the design cycle. While these advantages involve trade offs
between power consumption and digital bandwidth, modern FPGAs provide designers much
greater flexibility in mitigating power consumption, including the support of selectable core
voltages, or critical-path power analyses.
The greater the numbers of on-chip resources available in FPGAs, the more designers
are enabled to incorporate polyphase filtering and downconversion in the digital domain.
Multiple onboard or external numerically controlled oscillators (NCOs) can allow very high
phase discrimination with high-capacity FPGA devices. This application is useful for
prototyping, research and development, where designers can incorporate and test multiplephase
resolutions without significant hardware investments by using hardware-in-the-loop
test methodologies.

Fig3: Block diagram of a typical architechture for integrated polyphase filtering and
Examples of algorithmic math functions in radar systems include recursive least-square
and square-root operations. Many designers have implemented these functions in C-based
processors (in fixed-decimal and floating-point operations), or with proprietary FPGA VHDL
operations. The current generation of FPGA devices include embedded processor and logiccell
resources to efficiently implement these processes; future generations will also have
these capabilities. Additionally, IP cores and reference designs are becoming available to
transition anywhere from dozens to hundreds of these operations into a single FPGA.
Tools are available to translate processor-based algorithms from C code to hardware
languages, such as very high-level descriptive language (VHDL). These tools can be used to
optimize certain logic functions from a standard main processor into an FPGA co-processor
operating in parallel with the main processor, or to move entire operations from the main
processor to the FPGA hardware. This provides an additional dimension of flexibility to the
radar- or sonar-architecture designer's toolkit.

Matrix inversion is an important element of adaptive-array designs and standard spatialtransceiver-
array processing (STAP). These operations are commonly performed in fixed
hardware elements, though efficiently implemented embedded processing has been
demonstrated in some radar/sonar development programs. The logic-element size and
potential parallelism of a matrix inversion engine depends on the size of the array used in the
radar system. As the size of the array is increased, so does the number of floating-point
multiplications required by the system. Therefore, in larger arrays, there are more trade-off
options between the speed of the system and the number of logic elements required by the
system (both of which increase as the parallelization of the architecture increases).
Implementing this function using a combination of a DSP and a group of internal memory
blocks is the most likely design path for radar-system designers. As these operations are often
tailored to the adaptive-array algorithms of the radar system, they are likely to be custom
designed in VHDL. However, reference designs that are optimized for the place-and-route
capabilities of an FPGA device can be offered or designed to order from the FPGA
manufacturer, if required for the radar or sonar system.
The bandwidths of many systems, including radar/sonar and test/measurement systems,
are beginning to exceed the capabilities of dedicated DSPs. Implementing fast-Fourier
transforms (FFTs) and their inverses in FPGA logic has advantages in prototyping and
scalability, and offers design flexibility between a system's speed and the number of required
logic elements. For example, massively parallel implementations can be designed and
distributed among the logic elements of a single or multiple FPGAs. However, while these
implementations can significantly reduce latency, they impose the penalty of a greater
number of logic elements.

In fact, the primary flexibility advantage of an FPGA for FFTs is the ability to select
the optimal balance between these two parameters in the initial design. This is fortunate,
because the implementation of large or complex FFTs should be the primary factor in any
design, and the advantages of an FFT implementation in an FPGA are apparent. However,
creating code or modifying existing code from previous designs can be cumbersome when
testing and verifying code units. Therefore, what is needed is a comprehensive suite of FFT
design tools that allows a nearly infinitely scalable FFT design. These tools should allow
scripted logic distribution among multiple FPGAs where necessary. They should also be able
to automatically generate numerical coefficients having floating-point accuracy. Customer
inputs are being taken now for such tools.
Because radar, sonar and digital-communication system designers must focus on the
complications of multi-element beam-forming and waveform generation not FFT design,
programmable logic vendors such as Altera have internal tools and generators for conducting
large, difficult element transformations. This includes reference designs and core IP wizards
for standard and non-standard designs, as well as FFT co-processors, which are important
design aids in the programmable logic offering.
Fig 4: Block diagram for an FPGA-based FFT implementation.

DSP logic designs are commonly executed from an initial model in simulation
languages, such as Matlab or Simulink. These models are the most common, but not the only
sources for designers to access optimized DSP IP offered through FPGA providers. The
linkage between modeling and hardware implementation is important, not only for design
simplicity, but for simulation and verification against the model. As the design density for
FPGA-based sensor systems increase, full system modeling and simulation will become more
time consuming. Compile, simulation, and place- and-route times will increasingly become
discriminators when selecting FPGA and design-software vendors. Furthermore,
multiprocessor and distributed processing options for design software will be necessary to
keep up with design complexity.
To cope with these trends, and to achieve the greatest signal-processing performance in
their sonar or radar systems, designers are encouraged to consider options beyond their own
VHDL modules or other internally developed IP. Specifically, they should consider working
with programmable logic manufacturers to develop tailored DSP cores, or find ways to
improve and optimize their designs through advanced place-and-route methods available for
FPGA design tools. This is because the advanced capabilities of integrated circuits enabled
by increasingly sophisticated fabrication technologies cannot be fully harnessed without
flexible and effective design techniques.


FPGA-based radar signal processing for a new generation automotive Driver
Assistance system has been discussed in this paper. There is a lot of researches are going on
in the field of Driver Assistance system. Automotive industry is increasingly enthusiastic to
include radars in future vehicles. Automotive industry now look for consumers to become
increasingly comfortable with driver aids and demand more relief from the tedium of driving
and look for the technology to deliver.
Radar and digital signal processing are the key components of Driver Assistance
system. FPGAs have been used in radar based Driver Assistance systems for some time,
mostly in support functions. However, as FPGAs get more sophisticated, performing and
integrating more DSP functions in FPGAs is becoming the standard . FFT are the key
techniques for analysing the digital signal. The recent advances in signal processing are
blended with many more algorithms to present an up-to date perspective and can be
implemented in Digital Signal Processor because of their flexibility and the ability to attain
high precisions.
DSP and FPGA solutions provide designers with a myriad of implementation options
and solutions for today’s system designs. Along with these solutions comes a variety of
design factors and considerations that need to be evaluated to select the best approach,
depending on system requirements like ease of implementation, cost and performance as well
as power consumption. Digital signal processors can provide the simplest implementation for
a wide range of DSP algorithms and applications, but the cost/performance, implementation
flexibility and hardware parallelism provided by an FPGA cannot be overlooked. From a
price/performance comparison, FPGAs provide better performance for lower cost compared
to a DSP approach. Additionally, if the FPGA is not fully utilized, more functionality and
parallelism could be added to the FPGA to increase the amount of processing the FPGA is
capable of without impacting the cost of the system. Also, from a function-to-function power
comparison, we see that for the same function, an FPGA implementation is capable of
consuming less power than a digital signal processor.


1. Jean Saad , Amer Baghdadi, Frantz Bodereau, “FPGA based Radar signal processing
for Automotive Driver Assistance System”, IEEE/IFIP International Symposium on
Rapid System Prototyping,vol.40,no.2, pp.196-199, November 2009.
2. Stove, A.G., “Linear FMCW radar techniques”, IEEE transactions on Radar and Signal
Processing, vol.139, no.5, pp.343-350, Oct 2007.
3. Basten, M. J., “Low Cost Implementation of an ACC Automotive Radar”, Institution
of Engineering and Technology Seminar on MM-Wave Products and Technologies,
vol.49, no.6, pp.1-6, Sept 2007.
Active In SP

Posts: 1
Joined: Dec 2010
08-12-2010, 11:30 AM

Which FPGA has been used?
which code has been used for pulse xmission?
pls reply.
science projects buddy
Active In SP

Posts: 278
Joined: Dec 2010
23-12-2010, 09:45 AM

As far i see it, the author has just studied about the use of FPGA for DSP application(Radar signal processing application here.)No specific FPGA has been specified and the general advantages of using FPGA for DSP has been discussed.

This is a seminar and presentation report only and hence no code has been written, only the system has been studied.
Use Search at http://topicideas.net/search.php wisely To Get Information About Project Topic and Seminar ideas with report/source code along pdf and ppt presenaion

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