ECCM – RADAR PROBLEMS

Jammers are typically barrage noise or repeater jammers. The former try to prevent all radar detections whereas the latter attempt to inject false targets to overload processing or attempt to pull trackers off the target.

A standoff jammer attempts to protect a penetrating aircraft by increasing the level of noise in the radar’s receiver. In such an environment, the radar should be designed with electronic counter countermeasures.

These can include adaptive receive antennas (e.g., adaptive array or sidelobe canceler), polarization cancelers (defeated easily by jammer using independent jamming on horizontal and vertical polarizations), sidelobe blankers to prevent false pulses through the sidelobes, frequency and prf agility to make life more difficult for the repeater jammer, low probability of intercept (LPI) waveforms, spread spectrum waveforms that will decorrelate CW jammers, spoofer waveform with a false frequency on the leading edge of the pulse to defeat set-on repeaters or a spoofer antenna having an EIRP that covers the sidelobes of the main antenna and masks the transmitted pulses in those directions, receiver uses CFAR/Dicke-fix, guard band blanking, excision of impulsive noise in time domain, and excision of narrow-band jammers via the frequency domain, etc.

In stressing cases, the radar can employ burn through (i.e., long dwells with noncoherent integration of pulses). Bistatic radars can also be used to avoid jamming. For example, a standoff (sanctuary) transmitter can be used with forward-based netted receive-only sensors [avoid antiradiation missiles (ARMs) and responsive jammers] to located targets via multilateration.

Ultralow sidelobe antennas can be complemented with remote ARM decoy transmitters that cover the radar’s sidelobes. Adaptive antennas include both adaptive arrays and sidelobe cancelers. The adaptive array includes a number of low-gain elements whereas the sidelobe canceler has a large main antenna and one or more low-gain auxiliary elements having sufficient gain margin to avoid carryover noise degradation.

The processing algorithms are either analog (e.g., Applebaum orWidrow LMS feedback) that can compensate for nonlinearities or are digital (sample matrix inversion or various eigenvector approaches including Gram–Schmidt and singular valved decomposition (SVD)). Systolic configurations have been implemented for increased speed using Givens rotations or Householder (conventional and hyperbolic) transformations.

In a sidelobe canceller (SLC) the jamming signal is received in the sidelobe of the main antenna as well as in the low-gain auxiliary element. By weighting the auxiliary signal to match that of the main antenna and setting the phase difference to 180◦, the auxiliary signal can be added to the main channel yielding cancellation of the jammer.

The weighting is determined adaptively since the main antenna is usually rotating. Target returns in the mainbeam are not canceled because they have much higher gain than their associated return in the auxiliary antenna. Since they are pulsed vs. the jammer being continuous, target returns have little effect in setting the adaptive weight. Since the closed-loop gain of an analog canceler is proportional to jamming level, the weights will converge faster on larger jammers creating an eigenvalue spread.

To prevent the loop from becoming unstable, receiver gains must be set for a given convergence time on the largest expected jammer. Putting limiters or AGC in the loops will minimize the eigenspread on settling time. The performance of jammer cancellation depends on the nulling bandwidth since the antenna pattern is frequency sensitive and the receivers may not track over the bandwidth (i.e., weights at one edge of the band may not yield good nulling at the other end of the band).

Broader bandwidth nulling is achieved through more advanced space-time processing; that is, channelize the spectrum into subbands that are more easily nulled or, equivalently, use adaptive tapped delay lines in each element to provide equalization of the bandpasses; that is, the adaptive filter for each element is frequency sensitive and can provide the proper weight at each frequency within the band.

A Frost constraint can be included in digital implementations to maintain beamwidth, monopulse slope, etc., of the adapted patterns. If the jammers are closely spaced, mainlobe nulling may be required. Nulling the jammer will cause some undesired nulling of the target as the jammer-target angular separation decreases.

This is limited by the aperture resolution. Difference patterns can be used as auxiliary elements with the sum beam. The adaptation will place nulls in the mainlobe of the sum pattern. They are actually more like conical scan where a difference pattern is added to a sum pattern to move the beam over.

The mainbeam squints such that the jammer is placed in the null on the side of the mainbeam. Better angular resolution can be achieved by nulling with two separated array faces. The adaptive pattern can now have sharp nulls that cancel jammers with minimal target loss since the angular resolution is set by the much wider interferometric baseline.

RADAR CLASSIFICATION AND IMAGING BASIC INFORMATION

Classification

Many instrumentation and early warning/BMD radars perform object classification based on radar signature measurements, for example, sorting reentry vehicle (RV) vs. decoy. This is usually obtained through deceleration of the body by the atmosphere, wake effects (mean and spread), micro dynamic motion (nose tip precession), polarization, range profile, inverse synthetic aperture radar (ISAR) imaging, radar cross-section (rcs) statistics, etc.

Typical estimators include Bayesian approaches. The K factor describes the ability to resolve two types of objects, that is, the separation of their probability density functions normalized to the spread of the density function.

Many lightweight traffic decoys (e.g., balloons) can be placed on a post boost vehicle (PBV) by replacing an RV, but the ability of the lightweight decoy to penetrate the defense is less than that of a heavier replica decoy. Munkers algorithm can be used for optimally assigning objects seen on one sensor to those seen by another sensor, that is, handover or target object mapping (TOM).

Much work has been performed in the past in identifying or classifying battlefield vehicles (e.g., truck, jeep, tank) based on high-range resolution measurements. A priori measured range profiles at various angles can be stored to be matched against by an unknown object.

Sometimes features are extracted from the data such as spacing between largest spikes, order of magnitude of spikes, etc. Some of the work has involved the use of neural networks.

Imaging

The simplest imaging radars use high range resolution with Doppler processing, that is, FFTs within the range cells. For a rotating object, the Doppler frequency increases with distance from the axis of rotation and hence, maps cross range intoDoppler to produce two-dimensional ISAR images.

Range walk will limit Doppler resolution since it determines how many pulses can be processed in the Doppler filter. The crossrange resolution is related to the angle through which the target rotates during the coherent processing.

ISAR is similar to the conventional noncoherent tomography (radon transform, back projection) used in X-ray processing. Since it is only the relative motion between radar and target that is important, the turning object in ISAR is equivalent to a stationary target and a synthetic circular SAR, that is, aircraft flying a circle about the target.

More advanced ISAR imaging radars use polar processing to avoid the range walk problem. The most advanced imaging radars use extended coherent processing where an image is created by coherently overlaying images for several complete rotations of the object. Maximum entropy method(MEM) techniques can be used to extend the bandwidth to provide sharper images for a given actual RF bandwidth.

Airborne synthetic imaging radars (i.e., conventional SAR) use a small aperture on a moving platform. By storing the pulses and coherently combining them, a large synthetic array can be constructed that is focused at all ranges.

The effective synthetic pattern is actually a 2-way pattern and the cross-range resolution at every range is about the same as the size of the physical antenna on the aircraft. At each range, the phases from a scatterer produces a quadratic runout (i.e., LFM) that varies with range.

Each range cell is match filtered yielding a pulse compression in the azimuth direction. Since Doppler frequency is mapping into cross range, moving objects such as a train create a range-Doppler coupling and may image off the tracks.

Stereoscopic imaging can be performed by using SAR mapping from two aircraft ormultiple displaced apertures on the same aircraft. The phase difference in a common pixel for the two apertures will provide height data within the pixel.

RADAR ACCURACY AND RESOLUTION BASIC INFORMATION

Accuracy relates to a measurement or prediction being close to the true value of target parameters. Precision relates to the fineness of the measurements, which may not be very accurate, but could be quite precise.

Target parameters for which accuracy is important include range, angle, Doppler, and amplitude. Accuracy varies as a function of range. At long range, thermal noise effects tend to dominate.

At intermediate ranges, accuracy is dominated by the instrumentation errors (relatively constant vs. range). At short ranges, angle glint effects can dominate since the angular extent of the target increases inversely with range.

The accuracy of a given measurement due to thermal noise is given by σ = K/√SNR where K has the same dimensions as the measurement, but is also inversely proportional to the effective width in the other domain of a Fourier transform (FT) pair (i.e., range or time has frequency or bandwidth as its FT pair).

Hence, the K for a range measurement is inversely proportional to bandwidth and the K for a Doppler frequency measurement is inversely proportional to time extent of the waveform, that is, takes a long time to discern small differences in frequency.

Since an antenna pattern is the FT of its aperture distribution, the K for angle accuracy is inversely proportional to effective aperture width. Resolution pertains to the question: Is there one target present or many? If two targets are resolved in range (i.e., well separated compared to the compressed pulse width), there will be two distinct returns.

As the targets get closer together, the returns begin to merge such that it is difficult to tell if there is one or two since the thermal noise tends to distort the combination. The presence of a dip between them yielding two peaks will depend on the relative phases of the two pulses.

Typical resolution algorithms include the classical inflection or dip approach, as well as template matching algorithms that look for differences compared to the known response of a single point target. Multipath and thermal noise will affect the probability of correctly resolving two targets in range when two targets are present as well as the probability of false splits (i.e., claiming that two targets are present when only one is actually present).

Similar algorithms are used for resolution in angle when the beam scans past the target. If frequency diversity is used on different prfs, this will cause the amplitude to fluctuate as the beam scans past the target making it even more difficult to determine whether there is one or two targets present.

With a monopulse radar, one can examine the imaginary part of the complex mono pulse ratio to determine if more than one target is present. A single target creates a quadrature value of zero, and multiple targets can create a nonzero value.

RADAR TRACKING BASIC INFORMATION

Tracking involves both data association and the process of filtering, smoothing, or predicting. Data association involves determining the origin of the measurements (i.e., determine whether a return is a false alarm, clutter, or a valid target and assess which returns go with which tracks or is this the first return from a given target).

Given that the return is properly associated, an algorithm is needed to include this latest measurement in a manner that will improve the estimate of the next expected position of the target. Early trackers, such as the alpha-beta-gamma filter, used precomputed fixed gains that were sometimes changed based on maneuver detection.

They were simple to code and required small amounts of memory and throughput. As tracking advanced, radars began to use the EKF.Many filter states were used in ballistic missile defense (BMD) and early warning trackers.

More modern tracking approaches use non uniformly scheduled pulses, Kalman filtering of multiple sensors, nonlinear filters, interacting multiple model (IMM), joint probabilistic data association (JPDA), and multiple hypothesis tracking (MHT).

Decision-directed techniques, such as MHT, can result in a growing memory that must be pruned as possibilities are deemed unlikely. As target density or clutter increases, many false tracks can initiate but over time it becomes obvious which are actual and which are bogus.

The Hough transform can be used to track/detect straight line trajectories or those generalized for curvature. Phased arrays provide flexibility for minimizing the energy to track targets with a given accuracy or impact point prediction (IPP).

Options include revisit interval, dwell time, and beam width spoiling. A tracking radar can use a high prf that avoids range blindness on the tracked target while providing ample Doppler space free of clutter.

If a search radar is ambiguous in range, a different prf must be used on each dwell to resolve range ambiguities. If a target is within the unambiguous range interval, the range cell where the detection occurs does not change. If the target is beyond the range ambiguity distance, the range cell number changes due to the range fold over.

The Chinese remainder theorem can be used to unravel the true range based on several ambiguous range measurements. The range estimate, however, can be grossly in error if an unambiguous range cell number is off by a single range cell due to measurement noise.

Other approaches of resolving range ambiguities avoid this problem. For example, the entire instrumented range can be laid out for each dwell with a return placed at all corresponding ambiguous range cells.

By summing the dwells in each range cell, the one with the highest count will be the true range since they all occur in this cell. To prevent errors due to a slight range error, one can sum both the range cell and its adjacent neighboring cells over all dwells.

This will ensure that slight misses will be correctly counted in the summation. Methods that resolve range ambiguities for a point target are not very effective for a weather radar where the target is distributed. Multiple targets can produce ghosts when unraveling unambiguous ranges.

APPLICATIONS OF RADIO DETECTION AND RANGING (RADAR)

Radars can be classified by frequency band, use, or platform, for example, ground based, shipborne, airborne, or spaceborne. Radars generally operate in the microwave regime although HF over-the horizon (OTH) radars such as JINDALEE, OTHB, and ROTHR use similar principles in bouncing signals from the ionosphere to achieve long-range coverage.

Radars are often denoted by the letter band of operation, for example, L-band (1–2 GHz), S-band (2–4 GHz), C-band (4–8 GHz), and X-band (8–12 GHz). Some classifications of radar are based on propagation mode (e.g., monostatic, bistatic, OTH, underground) or on scan method (mechanical, electronic, multibeam).

Other classifications of radar are based on the waveform and processing, for example, pulse Doppler (PD), continuous wave (CW), FM/CW, synthetic aperture radar (SAR) or impulse (wideband video).

Radars are often classified by their use: weather radar, police speed detection, navigation, precision approach radar, airport surveillance and air route surveillance, radio astronomy, fire control and weapon direction, terrain mapping and avoidance, missile fuzing, missile seeker, foliage penetration, subsurface or ground penetrating, acquisition, orbital debris, range instrumentation, imaging (e.g., SAR/ISAR), etc.

Search (or surveillance) radars are concerned with detection of targets out to long range and low elevation angles to allow adequate warning on pop-up low-flying targets (e.g., sea skimmers). Since the search radar is more concerned with detection (i.e., presence or absence of targets) and can accommodate cruder accuracy in estimating target parameters such as azimuth angle, elevation angle, and range, search radars tend to have poorer range and angle accuracy than tracking radars.

The frequency tends to be lower than track radars since RF power and antenna aperture are less expensive and frequency stability is better. Broad beams (e.g., fan beam) allow faster search of the volume.

To first order, the radar search performance is driven by the power-aperture product (PA) to search the volume with a given probability of detection (PD) in a specified frame time. PA actually varies slightly in that to maintain a fixed false alarm rate per scan, more beam positions offer more opportunities for false alarms and, hence, the detection threshold must be raised, which increases the power to achieve the specified PD.

With a phased-array antenna (i.e., electronically scanned beam), the probability of false alarm can be optimized by setting a high false alarm in the search beam and using a verify beam with higher threshold to confirm whether a search detection was an actual target or just a false alarm.

The lower threshold in search allows less search power with some fraction of beams requiring the extra verify beams. The net effect on total required transmit power can be a reduction using this optimization technique.

Search radars tend to use a fan beam or stacked receive beams to reduce the number of beam positions allowing more time in the beam for coherent processing to reduce clutter. Fill pulses are sometimes used to allow good clutter cancellation on second- or higher time-around clutter returns.

Track radars tend to operate at higher frequency and have better accuracy, that is, narrower beams and high range resolution. Simple radars track a single target with an early–late range tracker, Doppler speed gate, and conical scan or sequential lobing.More advanced angle trackers use monopulse or conical scan on receive only (COSRO) to deny inverse modulation by repeater jammers.

The multifunction phased-array radar can be programmed to conduct searches with track beams assigned to individual detected targets. The tracks are maintained in track files. If time occupancy becomes a problem, the track pulses can be machine gunned out at the targets in range order, and on receive they are gathered in one after the other since the track window on each target is quite small.

In mechanically rotated systems, track is often a part of search, for example, track-while-scan (TWS). A plot extractor clusters the primitive returns in range Doppler angle from a given target to produce a single plot.

The plots are associated with the track files using scan-to-scan correlation gates. The number of targets that can be handled in a TWS system is limited by data processing rather than track power.

RADIO DETECTION AND RANGING (RADAR) APPLICATIONS BASIC AND TUTORIALS

Radars can be classified by frequency band, use, or platform, for example, ground based, shipborne, airborne, or spaceborne. Radars generally operate in the microwave regime although HF over-the-horizon (OTH) radars such as JINDALEE, OTHB, and ROTHR use similar principles in bouncing signals from the ionosphere to achieve long-range coverage.

Radars are often denoted by the letter band of operation, for example, L-band (1–2 GHz), S-band (2–4 GHz), C-band (4–8 GHz), and X-band (8–12 GHz). Some classifications of radar are based on propagation mode (e.g., monostatic, bistatic, OTH, underground) or on scan method (mechanical, electronic, multibeam).

Other classifications of radar are based on the waveform and processing, for example, pulse Doppler (PD), continuous wave (CW), FM/CW, synthetic aperture radar (SAR) or impulse (wideband video). Radars are often classified by their use: weather radar, police speed detection, navigation, precision approach radar, airport surveillance and air route surveillance, radio astronomy, fire control and weapon direction, terrain mapping and avoidance, missile fuzing, missile seeker, foliage penetration, subsurface or ground penetrating, acquisition, orbital debris, range instrumentation, imaging (e.g., SAR/ISAR), etc.

Search (or surveillance) radars are concerned with detection of targets out to long range and lowelevation\ angles to allow adequate warning on pop-up low-flying targets (e.g., sea skimmers). Since the search radar is more concerned with detection (i.e., presence or absence of targets) and can accommodate cruder accuracy in estimating target parameters such as azimuth angle, elevation angle, and range, search radars tend to have poorer range and angle accuracy than tracking radars.

The frequency tends to be lower than track radars since RF power and antenna aperture are less expensive and frequency stability is better. Broad beams (e.g., fan beam) allow faster search of the volume. To first order, the radar search performance is driven by the power-aperture product (PA) to search the volume with a given probability of detection (PD) in a specified frame time.

PA actually varies slightly in that to maintain a fixed false alarm rate per scan, more beam positions offer more opportunities for false alarms and, hence, the detection threshold must be raised, which increases the power to achieve the specified PD.With a phased-array antenna (i.e., electronically scanned beam), the probability of false alarm can be optimized by setting a high false alarm in the search beam and using a verify beam with higher threshold to confirm whether a search detection was an actual target or just a false alarm.

The lower threshold in search allows less search power with some fraction of beams requiring the extra verify beams. The net effect on total required transmit power can be a reduction using this optimization technique. Search radars tend to use a fan beam or stacked receive beams to reduce the number of beam\ positions allowing more time in the beam for coherent processing to reduce clutter. Fill pulses are sometimes used to allow good clutter cancellation on second- or higher time-around clutter returns.

Track radars tend to operate at higher frequency and have better accuracy, that is, narrower beams and high range resolution. Simple radars track a single target with an early–late range tracker, Doppler speed gate, and conical scan or sequential lobing.

More advanced angle trackers use monopulse or conical scan on receive only (COSRO) to deny inverse modulation by repeater jammers. The multifunction phased-array radar can be programmed to conduct searches with track beams assigned to individual detected targets.

The tracks are maintained in track files. If time occupancy becomes a problem, the track pulses can be machine gunned out at the targets in range order, and on receive they are gathered in one after the other since the track window on each target is quite small. In mechanically rotated systems, track is often a part\ of search, for example, track-while-scan (TWS).

A plot extractor clusters the primitive returns in range Doppler angle from a given target to produce a single plot. The plots are associated with the track files using scan-to-scan correlation gates. The number of targets that can be handled in a TWS system is limited by data processing rather than track power.