ISAR imaging using an emulated multistatic radar system

The use of a monostatic radar configuration limits the ability of an inverse synthetic aperture radar (ISAR) system to image targets in certain geometries. By employing multistatic geometries this limitation may be overcome. This paper discusses the emulation of multistatic geometries, via sea surface multipath reflections, using a monostatic system. This application capitalises on the advantages provided by both monostatic and bistatic systems. The possibility of obtaining ISAR images using these emulated multistatic radar configurations is first theoretically discussed and then verified using experimental results.     

Comparison between monostatic and bistatic antenna configurationsfor STAP

The unique characteristics of bistatic radar operation on the performance of airborne/spaceborne moving target indicator (MTI) radars that use space-time adaptive processing (STAP) are discussed. It has been shown that monostatic STAP radar has the following properties. 1) For a horizontal flight path and a planar Earth the curves of constant clutter Doppler (isodops) are hyperbolas. 2) For a sidelooking antenna geometry the clutter Doppler is range independent. 3) Clutter trajectories in the cosφ-F plane (F=normalized Doppler) are in general ellipses (or straight lines for a sidelooking array). We demonstrate that these well-known properties are distorted by the displacement between transmitter and receiver in a bistatic configuration. It is shown that even for the sidelooking array geometry the clutter Doppler is range-dependent which requires adaptation of the STAP processor for each individual range gate. Conclusions for the design of STAP processors are drawn     

The Lunar Reconnaissance Orbiter Miniature Radio Frequency (Mini-RF) Technology Demonstration

The Miniature Radio Frequency (Mini-RF) system is manifested on the Lunar Reconnaissance Orbiter (LRO) as a technology demonstration and an extended mission science instrument. Mini-RF represents a significant step forward in spaceborne RF technology and architecture. It combines synthetic aperture radar (SAR) at two wavelengths (S-band and X-band) and two resolutions (150 m and 30 m) with interferometric and communications functionality in one lightweight (16 kg) package. Previous radar observations (Earth-based, and one bistatic data set from Clementine) of the permanently shadowed regions of the lunar poles seem to indicate areas of high circular polarization ratio (CPR) consistent with volume scattering from volatile deposits (e.g. water ice) buried at shallow (0.1–1 m) depth, but only at unfavorable viewing geometries, and with inconclusive results. The LRO Mini-RF utilizes new wideband hybrid polarization architecture to measure the Stokes parameters of the reflected signal. These data will help to differentiate “true” volumetric ice reflections from “false” returns due to angular surface regolith. Additional lunar science investigations (e.g. pyroclastic deposit characterization) will also be attempted during the LRO extended mission. LRO’s lunar operations will be contemporaneous with India’s Chandrayaan-1, which carries the Forerunner Mini-SAR (S-band wavelength and 150-m resolution), and bistatic radar (S-Band) measurements may be possible. On orbit calibration, procedures for LRO Mini-RF have been validated using Chandrayaan 1 and ground-based facilities (Arecibo and Greenbank Radio Observatories).     

Bistatic Interference between Neighboring Radars

Radar transmitters characteristically generate broadband noise sidebands [1] over the entire tunable frequency band of the system for the duration of the transmitted pulse. The noise will be backscattered over a substantial range interval. In certain circumstaces, this bistatic reflection of ground clutter emerges as the predominant mode of interference between adjacent radars operating in common bands. Closed form mathematical expressions are derived which relate this mutual interference to the system noise temperature. These results in turn are applied to a typical S-band radar.     

Statistical Technique for Radar Amplitude Calibration

A statistical technique for amplitude calibration of radar systems is presented. As distinct from the input-output crosscorrelation measurement of a linear system impulse response [1], this technique measures the amplitude transfer function of a memoryless, nonlinear system. A generalized theory is developed and calibration accuracy bounds are derived. Used in the calibration of a modern pulsed radar, the technique is compared with conventional reference pulse calibration. The relative merits of the deterministic and statistical approaches are compared.     

Theorem for the combination of bistatic radar measurements using least squares

In order to improve position finding performance, least squares method is often used to combine the measurement sets of bistatic radar system. However, which measurement sets can be combined by least squares method and which cannot have received little attention until now. We address this issue based on 2 measurements of bistatic radar system, for example (/spl rho/, /spl theta//sub T/), and present a new theorem, with proof, which shows that the least squares estimator can be obtained by combining any two measurement sets if these measurement pairs are disjoint. We provide an example that satisfies this condition, which shows that the least square combination of measurement sets yield improved performance especially in the vicinity of the transmitter and the receiver.     

A Multistage Processing Algorithm for Disturbance Removal and Target Detection in Passive Bistatic Radar

The paper examines the problem of cancellation of direct signal, multipath and clutter echoes in passive bistatic radar (PBR). This problem is exacerbated as the transmitted waveform is not under control of the radar designer and the sidelobes of the ambiguity function can mask targets including those displaced in either (or both) range and Doppler from the disturbance. A novel multistage approach is developed for disturbance cancellation and target detection based on projections of the received signal in a subspace orthogonal to both the disturbance and previously detected targets. The resulting algorithm is shown to be effective against typical simulated scenarios with a limited number of stages, and a version with computational savings is also introduced. Finally its effectiveness is demonstrated with the application to real data acquired with an experimental VHF PBR system.     

Ground and airborne target detection with bistatic adaptivespace-based radar

We have demonstrated that by using adaptive space-time processing, it is possible to detect and locate slowly-moving targets immersed in strong ground clutter from a bistatic spaceborne radar     

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     

Adaptive cancellation method for geometry-induced nonstationary bistatic clutter environments

This paper describes and characterizes a new bistatic space-time adaptive processing (STAP) clutter mitigation method. The approach involves estimating and compensating aspects of the spatially varying bistatic clutter response in both angle and Doppler prior to adaptive clutter suppression. An important feature of the proposed method is its ability to extract requisite implementation information from the data itself, rather than rely on ancillary - and possibly erroneous or missing - system measurements. We justify the essence of the proposed method by showing its ability to align the dominant clutter subspaces of each range realization relative to a suitably chosen reference point as a means of homogenizing the space-time data set. Moreover, we numerically characterize performance using synthetic bistatic clutter data. For the examples considered herein, the proposed bistatic STAP method leads to maximum performance improvements between 17.25 dB and 20.75 dB relative to traditional STAP application, with average improvements of 6 dB to 10 dB.     

双基地及其联网系统的定位方法及精度分析

讨论的双基地系统中,发射站只起照射目标的作用,而接收站测量距离和、方位角及俯仰角。分析了双基地系统的目标定位方法和定位误差。通过分析定位精度在受控区域内的分布,提示了双基地系统的定位性能。文中对组网双基地系统的定位处理方法进行了讨论,其中采用WLS(Weighted Least Square)算法进行数据融合处理,仿真结果表明,联网双基地系统的定位精度大有提高。     

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     

Bayesian and Dempster-Shafer target identification for radarsurveillance

This paper considers the problem of target track identification in a radar surveillance system. To build a target identifier alongside a tracker, four features which are available for real-time processing in an air surveillance system are used here: target identity (TID) from a friend-and-foe identification (IFF) system, elevation measurement from the radar, target speed, and acceleration estimated by a tracker. These four features are combined to classify air targets into five different air target categories: friendly commercial, friendly military, hostile commercial (or unknown airline), hostile military, and false targets (clutter). Two popular statistic-based techniques, namely, the Bayesian and Dempster-Shafer methods, are applied to develop radar target identification algorithms for our application. Real-life as well as simulated air surveillance radar data are used to evaluate the practicality and effectiveness of this track identification approach in a radar surveillance system     

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     

基于先验知识及其定量评估的自适应杂波抑制研究

 为了改善训练样本数受限的非均匀杂波环境中的系统检测性能,研究了基于先验知识及其定量评估的自适应杂波抑制算法。提出了使用经真实杂波信息白化后的先验杂波协方差矩阵与单位矩阵之差的谱范数,来定量评估杂波先验知识的准确程度,并给出了真实杂波协方差矩阵未知时的矩阵谱范数估计方法。结合先验知识定量评估结果,获得了具有先验知识约束时的杂波协方差矩阵最大似然估计方法。分别基于多脉冲相参雷达以及空时自适应雷达进行了杂波建模,在此基础之上分析了算法性能。仿真结果证实了该算法优于使用样本协方差矩阵及先验杂波信息形成杂波抑制权值的性能。     

Low observable target motion analysis using amplitude information

In conventional passive and active sonar system, target amplitude information (AI) at the output of the signal processor is used only to declare detections and provide measurements. We show that the AI can be used in passive sonar system, with or without frequency measurements, in the estimation process itself to enhance the performance in the presence of clutter where the target-originated measurements cannot be identified with certainty, i.e., for “low observable” or “dim” (low signal-to-noise ratio (SNR)) targets. A probabilistic data association (PDA) based maximum likelihood (ML) estimator for target motion analysis (TMA) that uses amplitude information is derived. A track formation algorithm and the Cramer-Rao lower bound (CRLB) in the presence of false measurements, which is met by the estimator even under low SNR conditions, are also given. The CRLB is met by the proposed estimator even at 6 dB in a cell (which corresponds to 0 dB for 1 Hz bandwidth in the case of a 0.25 Hz frequency cell) whereas the estimator without AI works only down to 9 dB. Results demonstrate improved accuracy and superior global convergence when compared with the estimator without AI. The same methodology can be used for bistatic radar     

Further results on radar pointing error reduction using discreteextended Kalman filtering

A recently proposed method of reducing target glint errors in radar systems using extended Kalman filtering is further extended with the inclusion of and compensation for clutter effects. A discrete target model and discrete Kalman filter (DKF) are used. Simulation results demonstrating the DKF are presented, and the limits on the effectiveness of the method are investigated. The major advantage of the DKF is that it can be implemented in software in the digital processor of the radar, offering flexibility over continuous time filters. The ability of the filter to reduce clutter effects further demonstrates the usefulness of this technique for radar pointing error reduction     

Radar Target Pointing Error Reduction Using Extended Kalman Filtering

A new method of reducing target glint errors in radar systems is presented. The target is modeled as n reflectors whose magnitudes and phases are known. The reflector positions are described by a dynamical model driven by white Gaussian noise. The resulting vibrations of the target reflectors produce glintlike pointing errors in the radar system. An extended Kalman filter is developed to estimate the positions of the target reflectors; this information is used to substantially reduce the pointing error due to glint. Data illustrating this glint reduction is given. The model is extended by the inclusion of clutter effects modeled in the same fashion as the glint phenomenon. The results presented indicate the limits of usefulness of this technique as a function of both receiver noise and relative clutter amplitude.     

基于OTHR与纯角度传感器群数据关联的模式辨识与定位精度提升

 天波超视距雷达(OTHR)目标跟踪面临着"三低"(低检测概率、低数据率和低测量精度)和"多径"(多条传播路径)的挑战,因此传播模式的准确辨识与目标定位精度提升是改善跟踪能力的关键。首先利用纯角度传感器群获得目标地理位置的初步估计,然后采用极大似然估计建立了OTHR的传播模式和杂波模式的辨识规则,进而利用最小方差估计准则实现OTHR和纯角度传感器群的量测融合。仿真结果表明,此算法的模式辨识正确率很高,能明显提升方位角的测量精度,但是不能明显提升径向距的精度。     

机载MIMO雷达空时自适应杂波对消器

针对机载多输入多输出(MIMO)雷达杂波分布呈现空时耦合特性,提出一种空时自适应杂波对消器.利用机载MIMO雷达的脉冲回波数据,构造杂波对消器的系数矩阵.通过空时自适应杂波对消器的预处理,可以有效地抑制杂波,并通过与常规空时处理算法的级联,最终可以有效提高动目标的检测性能.实现了由传统地基雷达杂波对消器向机载运动平台的推广.仿真结果表明,这种自适应杂波对消器不仅适用于正侧视雷达,对于非正侧视雷达也同样适用.