MTI Optimization in a Multiple-Clutter Environment

A means of optimizing a moving target indicator (MTI) filter for rejecting several types of clutter, which are generated by different mechanisms such as by rain or the ground, is formulated. lt is found that the optimal performance of such a filter depends on the spectral density functions, average radar cross sections, and the relative mean Doppler frequencies of each type of clutter. lt is shown that the optimal improvement factor of such a filter is bounded by the weighted average (weighted in accordance with the radar cross sections of the clutter types) of the improvement factor for the individual clutter type. lt is also shown that the improvement factor of such a filter is a function of the relative mean Doppler frequency f0 between the clutter types. As f0 increases, the performance of the MTI system degrades. The worst improvement factor occurs when f0 is equal to half of the radar pulse-repetition frequency (PRF).     

Optimal polarimetric detection of radar target in a slowlyfluctuating environment of clutter

It is shown that in a situation where a radar target is distant enough from the radar and is included in a natural or artificial clutter environment in such a manner that the conventional detection methods fail, it is possible to improve the radar detection performance by using appropriate signal processing on two orthogonal polarization states. A CFAR (constant false alarm rate) polarimetric detection system based on the study of the polarization difference between clutter and target is proposed. Since the polarization state of the clutter echoes fluctuates slowly from cell to cell, an autoregressive model can be applied to the components of the polarization vector to predict the detection thresholds needed to follow the polarization state variation. The detection thresholds are determined to maintain a false alarm probability equal to 10^-6. The presence of a target registers as a significant variation of the estimation error of the polarization vector. Results obtained from measurements of simple and canonical targets with artificial clutter are presented, and these results validate the principle of polarimetric detection     

Time-frequency method for detecting an accelerating target in sea clutter

The authors design a time-frequency (TF) method for use in high-frequency surface-wave radar (HFSWR) for detecting a small accelerating target in sea clutter. The clutter is modelled by pseudo targets moving with Bragg velocity towards and away from the radar. The design is based on the Wigner distribution (WD) defined by Chan (type-III WD, in our terminology) rather than the WD defined by Claasen and Mecklenbrauker (1980) (2times type-I WD, in our terminology). Like the type-I WD, the type-III WD also concentrates a chirp signal onto a straight line in the TF plane. The type-III WD has the following advantages: 1) Its range of unambiguously measurable frequencies (RUMF) is [-pi,pi] rad/s, whereas for the type-I WD the RUMF is [-pi/2,pi/2] rad/s. 2) It allows a target separated from the clutter by pi rad/s to be detected, whereas the type-I WD coalesces such a target with the clutter and thereby mask it. An ambiguity function (AF) was defined corresponding to the type-III WD and use it to derive a smoothed type-III WD that mitigates the clutter. The smoothed type-III WD method is applied to real radar data and shown to be superior to the conventional Fourier transform method. The advantages of the type-III WD over the type-I WD are also demonstrated. The design principles laid out in the paper can also be used to develop a TF method for use in air traffic control radar (ATCR) for detecting an accelerating target in land clutter     

The Effect of Spectral Shape on Clutter Standard Deviation

Many radar systems now employ wideband waveforms and noncoherent averaging techniques to reduce the scintillation of the backscatter from ground clutter. The purpose of this paper is to quantify the effects of the wideband spectral shape on the clutter standard deviation after noncoherent averaging of the received signal. Relationships are developed which quantify the clutter standard deviation for any spectral shape and any ratio of transmitted band-width to processed bandwidth.     

Spiky sea clutter at high range resolutions and very low grazingangles

X-band (9.5-10.0 GHz) backscatter at near grazing incidence (0.2 deg) from the sea off the coast of Kauai, Hawaii, was measured with a radar characterized by a high spatial resolution in range (0.3 m) and a high temporal resolution (2000 Hz pulse repetition frequency (PRF)). Extensive amounts (over 20 min per measurement) of vertically and horizontally polarized sea clutter data were taken with upwind (UP) and crosswind (CR) transmit geometries during the collection campaign. Specific but representative examples of the clutter were statistically and phenomenologically analyzed over time scales varying from long (200 s), to intermediate (5 s), to short (50 ms), and over range swaths varying from full (160 m), to partial (30 m), to a single range cell (0.3 m). All analyses and results presented here are noncoherent, involving only the clutter amplitudes. Each type of clutter exhibited the characteristic spiky behavior which has come to be expected from microwave sea backscatter observed at low grazing angles and high range resolutions, while showing, between themselves, marked transmit geometry and polarization dependent contrasts, with the horizontally polarized clutter, measured with an UP transmit geometry, being especially notable for its frequently occurring, significant high frequency spectral content. Within the same clutter type, differences were observed in the probability distributions of radar cross sections (RCS) of spatially and temporally extended spiking events     

Clutter rejection and transmitter-receiver requirements in anairborne radar

Ground clutter rejection requirements imposed on the exciter transmitter-receiver units of multirole airborne radar are examined. Methods are given to determine the characteristics of the units, such as noise, spurious spectral lines level, and analog-to-digital converter (ADC) dynamics, in both high- and medium-pulse-repetition-frequency modes of operation. It is shown that the spectral noise does not depend on either the wave form or the Doppler bandwidth. The reference oscillator spectral noise must be about -155 dB_c/Hz. The level of spurious lines generally depends only on the duty cycle, and the requirement is -80 dB_c for each line. ADC requires 12 to 14 b. The high-frequency mode is the most promising for detecting targets with very low radar cross sections in head-on configuration (free clutter domain)     

Angle/Doppler estimation in heavy-tailed clutter backgrounds

This work describes new methods on the modeling of the amplitude statistics of airborne radar clutter by means of alpha-stable distributions. We develop joint target angle and Doppler, maximum likelihood-based estimation techniques from radar measurements retrieved in the presence of impulsive uncorrelated noise modeled as an alpha-stable random process. We derive the Cramer-Rao bounds (CRBs) for the additive Cauchy interference scenario to assess the best case estimation accuracy which can be achieved. In addition, we introduce a new joint spatial- and Doppler-frequency high-resolution estimation technique based on the fractional lower order statistics of the measurements of a radar array. Simulation results demonstrate that the proposed methods can be of interest in the study of space-time adaptive processing (STAP) for airborne pulse Doppler radar arrays operating in impulsive interference environments     

Pulse Doppler signature of a rotary-wing aircraft

Field measurements of a modified Sikorsky S-55 helicopter target were carried out to investigate rotary-wing aircraft Doppler radar signature phenomenology. The results of the data analysis with regard to classification and identification of the aircraft based on its signature are presented. It was found that using the Doppler radar return and appropriate feature extraction techniques, the helicopter's design features can be estimated. Target backscatter from the main rotor blades, tail rotor blades, or hub can be used for target detection, acquisition, and classification as a rotary-wing aircraft. The extraction of configuration and blade count features can further define the helicopter for identification     

Doppler Processor Rejection of Range Ambiguous Clutter

Doppler processors are used in radar to separate target returns from clutter. When the clutter is at a range farther than the unambiguous range of the radar, the ability to reject the clutter is degraded. In this article the degradation is analyzed for an N-pulse batch processor with Dolph weighting, and the results show how degradation varies with design sidelobe level.     

Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications     

Correspondence - Optimum Radar Signal for Detection in Clutter

It is shown that in order to maximize the detectability of a radar target in clutter whose Doppler is unknown and is uniformly distributed over the Doppler bandwidth a simple CW or narrowband signal is optimal. The optimality criterion is the average deflection coefficient, with the averaging being over target Doppler frequency. Most remarkably the result does not depend on the clutter spectrum but holds for any distribution of clutter energy with frequency.     

Multi-Target/Multi-Sensor Tracking using Only Range and Doppler Measurements

A new approach is described for combining range and Doppler data from multiple radar platforms to perform multi-target detection and tracking. In particular, azimuthal measurements are assumed to be either coarse or unavailable, so that multiple sensors are required to triangulate target tracks using range and Doppler measurements only. Increasing the number of sensors can cause data association by conventional means to become impractical due to combinatorial complexity, i.e., an exponential increase in the number of mappings between signatures and target models. When the azimuthal resolution is coarse, this problem will be exacerbated by the resulting overlap between signatures from multiple targets and clutter. In the new approach, the data association is performed probabilistically, using a variation of expectation-maximization (EM). Combinatorial complexity is avoided by performing an efficient optimization in the space of all target tracks and mappings between tracks and data. The full, multi-sensor, version of the algorithm is tested on simulated data. The results demonstrate that accurate tracks can be estimated by exploiting spatial diversity in the sensor locations. Also, as a proof-of-concept, a simplified, single-sensor range-only version of the algorithm is tested on experimental radar data acquired with a stretch radar receiver. These results are promising, and demonstrate robustness in the presence of nonhomogeneous clutter.     

Environment and Radar Operation Simulator

The environment and radar operation simulator (EROS) is a hardware system whose function is to produce realistic synthetic radar backscatter, incorporating both target and clutter. The simulator is electrically connected to a subject radar and responds in real time to the radar's antenna scan angle by producing the correct composite video signal.     

Reduced-rank STAP for high PRF radar

Due to the range ambiguity of high pulse-repetition frequency (HPRF) radars, echoes from far-range fold over near-range returns. This effect may cause low Doppler targets to compete with near-range strong clutter. Another consequence of the range ambiguity is that the sample support for estimating the array covariance matrix is reduced, leading to degraded performance. It is shown that space-time adaptive processing (STAP) techniques are required to reject the clutter in HPRF radar. Four STAP methods are studied in the context of the HPRF radar problem: low rank approximation sample matrix inversion (SMI), diagonally loaded SMI, eigencanceler, and element-space post-Doppler. These three methods are evaluated in typical HPRF radar scenarios and for various training conditions, including when the target is present in the training data     

A Rader Clutter Model: Average Scattering Coefficients of Land, Snow, and Ice

A model has been developed for average radar backscatter from terrain based on recent carefully controlled wide-bandwidth measurements of vegetation, snow-covered ground, and sea ice and on a comparison with measurements over North America by the Skylab S-193 scatterometer. The models for the thiree cases take the form ?° dB = A + B? + Cf+ Df?, 20° ? angle of incidence ? 70°, where the constants vary depending on polarization and terrain class. They also differ above and below a critical frequency (6 GHz for general terrain, 8 GHz for sea ice, and between 8 and 12 GHz for snow). For angles of incidence of 0° (vertical) and 10°, the model is of the form ?° dB = M(?) + N(?)f over the range 1 to 18 GHz. Hundreds of thousands of measurements contributed to the general (vegetated terrain) model, and smaller numbers contributed to the snow and sea ice models. Since 1974 all measurements have been made with University of Kansas microwave spectrometers. A brief discussion of fading shows that insufficient data are available to describe the ranges adequately.     

Performance bounds for hot and cold clutter mitigation

A new method is presented for describing the theoretical interference space-time covariance matrix that will be observed in an adaptive airborne radar system under specific topographical conditions. Both hot clutter that is induced by interfering sources and cold clutter that results from the radar transmitter are considered. This method incorporates phenomenology observed under site specific conditions as well as system effects such as array geometry, receiver filtering, and system bandwidth. Use of this formulation rather than sample data analyses that are generally employed enables one to infer performance bounds for site-specific, and thus generally, heterogeneous terrain that are tighter and therefore more meaningful than the thermal noise floor limit     

基于3DT的空时自适应单脉冲参数估计算法

空时自适应处理(STAP)是机载预警雷达抑制杂波和干扰的一项关键技术,而多普勒三通道联合自适应处理(3DT)是适合工程实现的降维(RD)STAP方法。STAP目标检测后还需进一步估计目标的角度参数,因此将自适应单脉冲(AM)技术引入3DT,提出了一种高精度联合估计目标速度与方位空间角的空时自适应单脉冲算法。理论分析与仿真实验结果表明,当目标多普勒频率偏离检测多普勒单元中心频率时,该算法能同时减少目标多普勒跨越损失和空时导引矢量失配损失,进而提高输出信杂噪比(SCNR),改善目标测角精度。