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Hm3114401445

  1. 1. Umoh, Gabriel Etim, Akpan, Aniefiok Otu / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1440-1445 Application Of Digital Signal Processing In Radar Signals Umoh, Gabriel Etim, Akpan, Aniefiok Otu Department Of Electrical/Electronics Engineering Faculty Of Engineering, Akwa Ibom State University Ikot Akpaden, Mkpat Enin, Lga Akwa Ibom State, Nigeria Department Of Physics Faculty Of Natural Andapplied Sciences, Akwa Ibom State University Ikot Akpaden, Mkpat Enin, L.G.A. Akwa Ibom State, NigeriaAbstract There has been explosive growth in pattern while at the receiver, DSP performs manyDigital Signal Processing theory and applications complex tasks, including STAP (space time adaptiveover the years. This research explores the processing) – the removal of clutter, and beamapplications of digital signal processing in Radar. forming (electronic guidance of direction).A survey on applications in digital signal The front end of the receiver for RADAR isprocessing in Radar from a wide variety of areas still often analog due to the high frequenciesis carried out. A review is done on basic involved. With fast ADC convertors-often multipleapproaching models and techniques of signal channel, complex IF signals are digitized. However,processing for different parameters and digital technology is coming closer to the antenna.extracting information from the received signal. We may also require fast digital interfaces to detectThe various techniques adopted at different antenna position, or control other hardware.stages of radar to obtain the target’s signature, is The main task of a radar‟s signal processoralso researched. is to make decisions. After a signal has been transmitted, the receiver starts receiving returnKeywords: Radar, Doppler, Digital Signal signals, with those originating from near objectsProcess (DSP), convolution, Clutter filters, arriving first because time of arrival translates intoScanning, Synthetic aperture radar (SAR), target range. The signal processor places a raster ofcancellers range bins over the whole period of time, and now it has to make a decision for each of the range bins asINTRODUCTION to whether it contains an object or not. Flexibility and versatility of digital This decision-making is severely hamperedtechniques grew in the front-end signal processing by noise. Atmospheric noise enters into the systemand the advent of integrated digital circuitry, high through the antenna, and all the electronics in thespeed signal processors were developed and radar‟s signal path produces noise too.realized. Radar continued to grow in the recent yearsby keeping the future developments in mind and Major blocks of modern radar systemwith better digital capability. Significant The major components of modern radar are thecontributions in DSP in Radar have been in MTI antenna, the tracking computer and the signalprocessing, Automatic Detection and extraction of generator. The tracking computer in the modernsignal, image reconstruction, etc. A case study of radar does all the functions. By scheduling theRadar Synthetic Vision System for Adverse appropriate antenna positions and transmittedWeather Aircraft landing is discussed. In this report signals as a function of time, keeps track of targetsan effort is made to identify the contribution of DSP and running the display system.in the advancement of Radars.METHODOLOGIES RADAR transmits radio signals at distantobjects and analyzes the reflections. Data gatheredcan include the potion and movement of the object,also radar can identify the object through its“signature” the distinct reflection it generates. Thereare many forms of RADAR – such as continuous,CW, Doppler, ground penetrating or syntheticaperture; and they are used in many applications,from air traffic control to weather prediction. In the modern Radar systems, digital signalprocessing (DSP) is used extensively. At thetransmitter end, it generates and shapes thetransmission pulses, controls the antenna beam Fig 1. Block Diagram of a Modern Radar system 1440 | P a g e
  2. 2. Umoh, Gabriel Etim, Akpan, Aniefiok Otu / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1440-1445Even if atmospheric attenuation can be neglected, position in azimuth and elevation. When thethe return from a distant object is incredibly weak. radar is tasked with surveying its sector andTarget returns often are no stronger than twice the tracking dozens of targets, there‟s a danger ofaverage noise level, sometimes even buried under it. either neglecting part of the search sector orIt is quite difficult to define a threshold for the losing a target if the corresponding trace recorddecision whether a given peak is noise or a real isn‟t updated in time. Time management servestarget. If the threshold is too high then existing to maintain a priority queue of all the tasks andtargets are suppressed, that is, the probability of to produce a schedule for the beam steeringdetection (PD) will drop. If the threshold is too low device. Power management is necessary if thethen noise peaks will be reported as targets, that is, transmitter circuitry runs the danger ofthe probability of false alarms (PFA) will rise. A overheating. If there‟s no backup hardware thencommon compromise is to have some 90% the only way of continuing regular operation isprobability of detection and a false alarm rate of 10 - to use less power when less power is required,6 . say, for track confirmation. It maintains a given PFA known as CFAR, for  Countering interference: Interference can be a)Constant False Alarm Rate. Rather than keeping the natural or b) man-made. Natural interference canthreshold at a fixed point, CFAR circuitry inspects be heavy rain or hail storms, but also variedone range bin after the other and compares the propagation conditions. Man-made interference,signal level found there with the signal levels found if created on purpose, is also called jamming andin its neighboring bins. If the noise level is rather is one of the means of electronichigh in all these (e.g. because of precipitation) the countermeasures.CFAR circuit will raise the threshold accordingly.Further tasks of the signal processor are: Detection of Signals Combining information: Secondary Detection is the process by which the surveillance radars like those located on airports presence of the target is sensed in the presence of can ask an aircraft‟s transponder for information competing indications which arise from background like height, flight number or fuel state. Pilots echoes (clutter), atmospheric noise, or noise may also issue a distress signal via the generated in the radar receiver. The noise power transponder. The ground radar‟s signal processor present at the output of the radar receiver can be combines this data with its own measurements of minimized by using filter, whose frequency range and angular direction and plots them all response function maximizes the output peak-signal together on the appropriate spot on the scope. to mean-noise (power) ratio is called matched filter. Forming tracks: By correlating the data sets We shall discuss the application of digital filtering which were obtained in successive scan cycles, to matched filters. the radar can calculate a flight vector which indicates an aircraft‟s speed and expected Fast Convolution Filter Implementation position for the next scan period. Airport radars (a) Dual pipeline FFTs matched Filter are capable of tracking hundreds of targets In this system, FFTs are pipelined and both simultaneously, and flight safety depends heavily the forward and reverse radix-r FFTs are on their reliability. Military tracking radars use implemented in hardware. Initial recording of the this information for gun laying or guiding data is done using input buffer (IB) memory and it missiles into some calculated collision point. takes „N/r‟ clock pulses to read N data points and „r‟ Resolving ambiguities in range or Doppler input rails. The amount of time „N/r‟ is called as one measurements: Depending on the radar‟s pulse epoch. It requires three epochs for the first data to be repetition frequency (PRF), the reading for completely filtered, and is delivered by one epoch range, Doppler or even both are ambiguous. The thereafter. In the dual FFT systems arbitrary data is signal processor is aware of this and selects a filtered sequentially with arbitrary reference different PRF when the object in question is functions selected from reference memory. measured again. With a suitable set of PRFs, ambiguities can be eliminated and the true target Drawback position can be determined. In many applications the same data set be Ground clutter mapping: Clutter is a collective filtered with several different filters, in this case term for all unwanted blips on a radar screen. only one forward transform is performed followed Ground clutter originates from buildings, cars, by several inverse transforms, it is possible to mountains etc, and a clutter map serves to raise eliminate one of the pipeline FFTs. This is desirable the decision threshold in areas where known since it would save a large amount of hardware. clutter sources are located. (b) Single forward FFT matched Filter Time and power management: Within a The data is first transformed and the result stored in window of some 60ox40o, phased array radars the temporary storage memory (TSM). The data is can instantly switch their beam position to any then multiplied by the filter function and inverse 1441 | P a g e
  3. 3. Umoh, Gabriel Etim, Akpan, Aniefiok Otu / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1440-1445transformed. This allows multiple readouts of theforward transformed data for the TSM and multiplefiltering of the same data set; the output of each Input Delayfilter will appear sequentially. [IPP]Drawback - Output The data at the output of the forward FFTare in digit reverse order, it is then corrected by +reading the data out of the TSM in digit reversedorder. The second FFT is performed the output is A two-pulse canceller is used if the clutterplaced into an output buffer, and to be read in a bit component (assuming DC only) remains constant inreversed order from the output buffer. a given range bin and can be eliminated byIt requires five epochs for the first data to be subtracting the output from two successive pulses.completely filtered, and is delivered by one epoch The transfer function of two-pulse canceller is equal 1thereafter. to 1  Z . And is equivalent to FIR digital filter with magnitude response sin (  / 2 ).(c) Single inverse FFT matched FilterA single inverse FFT is employed and the data is In practice, the clutter has a power spectrum thatread from the input buffer in digit reverse order. The covers frequencies above DC. The two-pulsedata is transformed and stored in TSM in normalorder, and then read out in bit reserve order. canceller will attenuate low frequency components but may not totally reject clutter. A three-pulseDrawback canceller with its transform function equivalent toComplex conjugation must be performed after each 1 2transform and stored. The digit reversed access to FIR filter is 0.5  z  0.5 z . This attenuatesthe IB is required and the IB maybe quite large further the components near DC.compared to TSM and may be difficult toimplement. Implementation of Clutter Filter(d) Reconfigurable FFT matched Filter The returns from the same range bin overThe FFT subsystem switches the inter-stage delay several pulses are linearly combined to form thelines to realize both forward and reverse transforms. output per IPP, each delay of  can be realizedForward transform: by routing the data through the using shift register.inter-stage delay memories (IDMs) in decreasing a. The direct implementation of the optimumorder. linear processor with N points requires NInverse transform: by sending data through the multiplications per output point. Since aIDMs in the increased order of size. The total different optimum processor is designed formemory of each stage is the number of delay lines each Doppler channel, the filter tap weights arememories. different for each channel. b. A simpler Suboptimum Processor is obtainedComparison of 4 matched filter systems by cascading a three-pulse cancellor with a The relative performance of dual pipeline bank of band-pass filters (implemented by amatched filter is fastest but requires two complete sliding FFT). N-point FFT requires N log 2 Npipeline FFTs hence more hardware is required.Single inverse transform matched filter has better multiplications; only log 2 N multiplicationsperformance over single forward transform matched are required per each Doppler Channel. Thusfilter and also doesn‟t require a double buffered significant hardware simplifications areoutput memory. Reconfigurable FFT matched filter possible with this scheme provided itsis preferred and chosen most of the times, it doesn‟t performance is adequate.require digit reserved to the IB and also doesn‟t E.g. moving Target Detectorrequire digital recording of TSM. MTI Signal ProcessingDoppler processing A major task in moving target indicator Doppler processing is used to filter out (MTI) radar is to obtain a time-domain filter, withclutter and thereby reveal fast moving targets. Such the introduction of digital technology, these arefilters are implemented digitally, FFT or a set of achieved using digital transversal filters, recursivetransversal filters. Cancellers and few optimized filters and filter banks.methods are some of the clutter rejection techniques. Adaptive Thresholding and Automatic DetectionCancellers Digital processing permitted the reference Clutter rejection filter amounts to the level to be generated/internally from thedesign of FIR digital filter with stop-bands to reject observations themselves, thereby permitting morethe clutter frequency component. A simple filter is a sensitive and faster thresholds. Most of the Radarstwo-pulse cancelor. employ automatic detection circuits to maintain, 1442 | P a g e
  4. 4. Umoh, Gabriel Etim, Akpan, Aniefiok Otu / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1440-1445ideally, a constant false alarm rate (CFAR) by The adaptive threshold CFAR processors isgenerating estimates of the receiver output. applicable to situations where the distribution of theAutomatic target detection for a search radar can be processed data (in the no-signal case) is knownachieved by comparing the processed voltage in generally and unknown parameters associated witheach cell to: the distribution can be estimated. It is often1. A fixed threshold level. implemented as moving or sliding window through2. Threshold levels based upon the mean amplitude which estimates of the unknown parameters of the of the ambient interference. interference are formed.3. A level computed on the basis of partial (a priori) knowledge of the interference distribution. B. Distribution free CFAR Processors4. A threshold level determined by distribution-free These provide CFAR characteristics when the statistical hypothesis testing that assumes no background return has an unknown distribution. prior knowledge of statistical distribution of the These processors remain insensitive to variations in interference. the distribution, and generally experiences In first case a detection decision is made if additional detection loss their CFAR propertiesthe processed signal ro , is equal or greater than a make their application advantageous. 1. Double Threshold Detectorpresent threshold. That is, if ro  T p , a detection is 2. Modified double threshold Detectordeclared. 3. Rank order DetectorThe second and third cases represent adaptive 4. Rank-sum double quantizer Detectorthreshold CFAR processors. In these processors,estimates of the unknown parameters of the known C. Scanning Radar Applicationdistribution of the processed interference are The optimum processor for a pulsed, non-coherentformed. In the second case can achieve CFAR when waveform on n pulses is a square law detectorthe distribution of processed interference is followed by a n pulse non-coherent integrator thatcompletely described by its mean level. The third uses equal weighting of each detected pulse. Thecase forms estimates of the unknown parameters of integrator must not only be realizable in practicalthe known (a priori) distribution. sense but alsoThe fourth case are called nonparametric CFAR 1. provide a small detection loss as possibleprocessors. These distribution-free process form a 2. provide a means of minimizing lossestest variable whose statistics are independent of the associated with integration sample windowdistribution of the input (non-processed) and scanning beam straddle of the targetinterference. 3. In track-while scan applications, permit accurate measurements of the target angularA. Adaptive Threshold CFAR Processors position. To adaptive Threshold CFAR Square law A/D Single Pulse IF signal ADDER Detector Convertor Delay Scaling Range gate Constant [kf] Fig.3 Square law detectorIntegrators that are typically configured are sliding Signal Processing in Synthetic Aperture Radarwindow. And this requires the storage of data for n (SAR)inter-pulse periods. The single-loop processor Digital processing has also permitted increasedrequires storage of data for the single inter-pulse capability for extracting target information form theperiod. Of course, if data memory is somehow radar signal. High resolution SAR provides anrestricted and if performance is acceptable the image of a scene. Radars are used to recognize onefeedback approach is preferred and single feedback type of target from another, with the aid of digitalloop is shown below. processing, inverse SAR (ISAR) produces an image 1443 | P a g e
  5. 5. Umoh, Gabriel Etim, Akpan, Aniefiok Otu / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1440-1445of a target good enough to recognize from other o ( vt x1 ) o ( vt x2 ) 2 2 j jclasses of targets by extracting the spectrum of a signal r (t )  e e cz1 cz1 is thetarget echo signal. Interferometric SAR, which usestwo antennas spaced vertically with a common SAR sum of two chirps. o [ 2 x1  x2 ) vt  x2  x1 ] 2 2system, can provide height information to obtain 3D jimage of a scene. Greater flexibility and real-time 1 e cz1 will be the signal of x1 isoperation suggest digital signal processing in SAR. considered as a reference point and is calledSAR exploits the probability density of the clutter to dechirping. The discrimination between the twodetect man-made features by modeling the clutter bya family of densities and picking the density that targets are performed analyzing x1 at zero frequencybest describes the clutter on local basis. and target x2 analyzed as frequencyFourier based methods are used for detection ofstationary and moving target detection and 2ov( x1  x2 ) / cz1 . Signal processing of theidentification in reconnaissance SAR. The multiplier of dechirping and FFT is carried out.computational time of the time domain correlator Since this approximation is done near to x1 the FFT(TDC) is overcome in the frequency domain. Here processing is limited to small region around thedigital spotlighting principle is used to extract the reference point. Also it is advantageous to band-target‟s coherent SAR signature. limit the dechirped azimuth signal to the frequencyStep 1 range of interest and do FFT. To avoid aliasing low-Coherent matched-filtered SAR reconstruction of pass filter is chosen whose impulse response is athe scene in the presence of foliage is developed by rectangular window and the frequency response isexploiting the angle and frequency from the target‟s Ncoherent SAR signature. sin / N sin  . The high frequency-domainStep 2 sidelobes of the rectangular window is overcome byWith the help of Fourier-based method the three using a different window or an optimal low-passdimensional statistic representing the moving target filter.coordinates and speed is used for moving target Thus this signal processing tends itself to a spotlightdetection. mode of SAR. Small areas of central reference pointStrip Mapping SAR are imaged individually and a large map isOn the incoming data, the pulse compression constructed by piecing together several sub-maps.matched filtering is done to obtain Range resolution The key feature to be considered to discriminate theand stored prior to azimuth processing. Data are man-made structure and the foliage is theprocessed one row at a time to perform the azimuth characteristics of SAR signature of a man madecompression, since large amount of data are metallic cylinder are different from the naturecollected large memory space is required. For each objects such as tree with the same size of lowrange resolution cell different azimuth compression frequencies in the UHF band.filter is required. Why not shape information to distinguishAssuming range azimuth resolutions are to be equal targets?and total range is mapped to  z then each memory The resolutions of the reconstructed SAR images are poor at UHF frequencies. The SAR magnitudecolumn has M samples and 2z1 / L samples 2 reconstruction of both man-made targets of foliage(niquist rate sampling) in each row. will appear as blobs. Thus, there is no muchThe total storage requirement is discrimination about the information. By the process 2 z 2Rmax of Digital spotlighting the procedure to extract theMemory   coherent SAR signature of a target is done. L L2 Target detection and identificationTotal calculation is that required for the operation of a. Matched Filter ReconstructionM azimuth pulse compression channels in parallel. Based on the SAR principles governing theSo the total computational time using direct variations of the gain and phase of target‟s coherentconvolution is upper- bounded by radar cross section with respect to the signal2MRmax frequency and relative speed, angle, we have a multiplications L2 general expression for the two-dimensional matchedBy using FFT for high speed convolution together filter that is capable of detecting a specified target inwith parallel parallelism reduces the speed the presence of foliage.requirement significantly. The measured signal S ( ku ) is passed through aSpotlight mode SAR bank of N, two-dimensional matched filters, and it isStretch processing is adopted, i.e., the azimuth passed through SAR wave front reconstructionresolution is obtained from different Doppler shifts algorithm.of the individual targets. Let x1 and x2 are the twotargets both at same range z1 then the received 1444 | P a g e
  6. 6. Umoh, Gabriel Etim, Akpan, Aniefiok Otu / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1440-1445b. Digital spotlight detection and integration aperture, multiple images are formed. Itidentification is then applied to two-dimensional adaptive filtersThe image filtered reconstruction requires image used for change detection to these multiple images.formation for all possible target types followed by a This had an advantage with the different responsessearch algorithm to detect the targets. The targets of clutter and targets with aspect angle. Clutterare identified by search method, extract the coherent returns were expected to show less aspect anglesignatures, and then perform matched filtering on dependency than targets, this property allows anglethe signature of these suspected targets. The dependency than targets, and clutter can be removedextraction of coherent signature from the coherent by change detection algorithms. This technique hasreconstruction image is done and process is called two distinct advantages over traditional changedigital spotlighting. detection the multiple aperture targets are perfectlyDigital spotlighting is a computer based process that co-registered and only one flight pass is requiredisolates the target or a target region in a SAR scene. over a given scene.To detect and identify targets, digital spotlightingthe reconstructed image f ( x, y ) is the CONCLUSIONreconstruction domain. A stationary target‟s In this research a brief overview of application ofsignature is fairly focused and once the target digital signal processing in Radar is presented.signature is spotlighted, it is transformed into any Matched filter implementation, echo cancellers anddomain of the SAR signal for identification. automatic detection and tracking are discussed inDetection of targets in foliage separate sections. In most of the modeling, FastThree different target detection techniques for UHF Fourier transform is a very commonly usedSAR were discussed in this research. These technique for analyzing and filtering digital signals.techniques are brief out. Different techniques of detection of targets ina. Baseline approach foliage are discussed for SAR. The recent advancesIt consists of 3 stages with high resolution, Ka-band in signal processing are blended with many moreSAR DATA. The first stage, a simple two-parameter algorithms to present an up-to-date perspective andconstant false alarm rate (CFAR) detector, is a can be implemented in Digital Signal Processorcomputationally simple prescreening algorithm that because of their flexibility and the ability to attainrejects most natural clutter. A target detection is high precisions.declared if the CFAR algorithm evaluation ratioexceeds CFAR threshold. This algorithm is followed REFERENCESby a clustering algorithm, which combines multiple 1. Alan V. Oppenheim, “Application ofdetections occurring in a target-sized area into a Digital Signal Processing”, Prentice Hall,single detection. The combination of these two Inc. Eaves Reedy, “Principles of Modernalgorithms is considered to be the baseline Radar”.algorithm. 2. Firooz Sadjadi, Mike Helgenson, Jeffb. Adaptive change detection Radke, Gunter Stein, “Radar SyntheticThe adaptive filters used are two-dimension Vision System for Adverse Weatherextensions of Widow Least mean Squares (LMS) Aircraft Landing”, IEEE Transactions onfilter, used as joint process estimators for noise Aerospace and Electronic Systems”, Jancancellation. Each makes use of two images, a 1999, Vol. 35, No. 1, pp. 2-15.primary, D [presumed to have targets] and a 3. Jeffrey G, Nanis, “Adaptive Filters forreference x [without targets]. The clutter of the Detection of targets in Foilage”, IEEE AESreference image is convolved with the weight Systems Magazin, Aug 1995, pp. 34-37.matrix, W, to predict the corresponding clutter in the 4. Lawrence R. Rabiner and Bernard Gold,primary image. This primary image is subtracted “Theory and Applications of Digital Signalfrom the primary to yield an error image, and the Processing”, Prentice Hall, Inc.difference is used to adoptively tune each element of 5. Mehradad Soumekh, “Reconnaissance withthe weigh matrix by an approximation. At each Ultra UHF Synthetic Aperture Radar”,iteration, the sign of the gradient is measured. After IEEE Signal Processing Magazine, Julyconsecutive sign changes, and scaling, the deviation 1995, Vol. 12, No. 4, pp. 21-39.is found. By using two-pass change detection with 6. P.E. Blankenship and E.M. Hofstetter,the adaptive filters, the target-to clutter ratio is “Digital Pulse Compression via Fastincreased. convolution”, IEEE Transactions Acousticc. Multiple aperture detection Speech and Signal Processing, VolumeIt takes off both the UHF SAR and the angular ASSP-23, April 1975, pp. 1898-201.diversity of target returns. In order to achieve a high 7. W.M. Brown and L.J. Porcello, “Ancross range resolution with a SAR operating at introduction to Synthetic Aperture Radar”,FOPEAN frequencies, it is necessary to process the IEEE Spect., Sept. 1969, pp. 952-62.data over a large integration angle. By splitting the 1445 | P a g e

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