Monopulse Estimation of the Centroid of an Ensemble of Radar Scatterers

The use of data obtained by a monopulse radar to estimate the location of the radar cross-section centroid of an ensemble of scatterers is discussed. Both dish and phased-array antenna radars are treated. Expressions for the bias and variance of the centroid estimates are presented, including the effects of the radar receiver and beam pattern characteristics, receiver noise, and the video waveform sampling granularity, as well as the target properties. The monopulse tracking approach discussed here is contrasted with a raster scan approach presented previously.     

Bayesian gamma mixture model approach to radar target recognition

This paper develops a Bayesian gamma mixture model approach to automatic target recognition (ATR). The specific problem considered is the classification of radar range profiles (RRPs) of military ships. However, the approach developed is relevant to the generic discrimination problem. We model the radar returns (data measurements) from each target as a gamma mixture distribution. Several different motivations for the use of mixture models are put forward, with gamma components being chosen through a physical consideration of radar returns. Bayesian formalism is adopted and we obtain posterior distributions for the parameters of our mixture models. The distributions obtained are too complicated for direct analytical use in a classifier, so Markov chain Monte Carlo (MCMC) techniques are used to provide samples from the distributions. The classification results on the ship data compare favorably with those obtained from two previously published techniques, namely a self-organizing map and a maximum likelihood gamma mixture model classifier.     

Improved target classification using optimum polarimetric SARsignatures

We present a new method for automatic target/object classification by using the optimum polarimetric radar signatures of the targets/objects of interest. The state-of-the-art in radar target recognition is based mostly either on the use of single polarimetric pairs or on the four preset pairs of orthogonal polarimetric signatures. Due to these limitations, polarimetric radar processing has been fruitful only in the area of noise suppression and target detection. The use of target separability criteria for the optimal selection of radar signal state of polarizations is addressed here. The polarization scattering matrix is used for the derivation of target signatures at arbitrary transmit and receive polarization states (arbitrary polarization inclination angles and ellipticity angles). Then, an optimization criterion that minimizes the within-class distance and maximizes the between-class metrics is used for the derivation of optimum sets of polarimetric states. The results of the application of this approach on real synthetic aperture radar (SAR) data of military vehicles are obtained. The results show that noticeable improvements in target separability and consequently target classification can be achieved by the use of the optimum over nonoptimum signatures     

Ten questions on UWB [ultra wide band radar]

Most radars now in use are narrow band systems with frequency bands much less than the carrier frequency. The theory and practice of current radar systems are based of this specific feature. But as is known, it is the frequency band that determines the information content of radar systems, as the volume of information transmitted per time unit is directly proportional to the frequency band. To raise the information capability of a radar system, the widening of its frequency band is needed. The only alternative approach is an increase in information transmission time. The actuality of this problem has determined rapid development in the last years of technologies using ultra wide band (UWB) signals. This paper describes the principles and features of UWB radar.     

Use of Airborne Monopulse Radar as a Low Approach Aid

The potential of airborne radar to provide pictorial displays as an aid to low approach has stimulated invention of several aircraft approach systems. Early developments are reviewed briefly, and an experiment in producing and flight testing a two-dimensional, range and azimuth, pictorial radar display is described. The monopulse radar equipment and a monopulse display improvement (MDI) technique used in the flight test to enhance the B-scope display are also described in some detail. Representative radar scope photographs are used to illustrate the display available in the aircraft.     

Adaptive imaging for forward-looking ground penetrating radar

Most of the current forward-looking ground-penetrating radar (FLGPR) systems use conventional delay-and-sum (DAS) based methods to form radar images for detection of the target (such as a landmine). However, DAS is a data-independent approach which is known to suffer from low resolution and poor interference and clutter rejection capability. We present a data-adaptive imaging approach for FLGPR image formation based on APES (amplitude and phase estimation) and rank-deficient RCB (robust Capon beamforming). Due to the data-adaptive nature of both APES and RCB, our approach has better resolution and much better interference and clutter rejection capability than the standard DAS-based imaging methods. The excellent performance of the proposed method is demonstrated using experimental data collected via two FLGPR systems recently developed by PSI (Planning Systems, Inc.) and SRI (Stanford Research Institute).     

Novel radar target detection

Herein, a novel method of radar target detection based on 2-dimensional (2-D) fractal dimension is proposed. The proposed approach exploits both range information and azimuth information to estimate fractal dimension. Moreover, the approach can increase the number of data points. The above two merits result in the fractal dimension estimated by this method are more accurate and robust than the previous method. The detection performance is also better than the previous, which only makes use of 1-dimensional (1-D) information to estimate fractal dimension. Theoretical analysis and experimental results show that the proposed method performs well in a strong clutter background. The proposed method is also validated by real-life radar data, and the better result has been achieved.     

Adapitive waveform design for distributed OFDM MIMO radar system in multi-target scenario

In order to improve detection and estimation performance of distributed Orthogonal-Frequency-Division Multiplexing (OFDM) Multiple-Input Multiple-Output (MIMO) radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design (AWD) based on a constrained Multi-Objective Optimization (MOO). The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.     

Radar target classification of commercial aircraft

With the increased availability of coherent wideband radars there has been a renewed interest in radar target recognition. A large bandwidth gives high resolution in range which means target discrimination may be possible. Coherence makes cross-range resolution and radar images possible. Some of the problems of classifying high resolution range profiles (HRRPs) are examined and simple preprocessing techniques which may aid subsequent target classification are investigated. These techniques are applied to HRRP data acquired at a local airport using the Microwave Radar Division (MRD) mobile radar facility It is found that Boeing 727 and Boeing 737 aircraft can be reliably distinguished over a range of aspect angles. This augers well for future target classification studies using HRRPs     

Stochastic-constraints method in nonstationary hot-cluttercancellation. I. Fundamentals and supervised training applications

This paper considers the use of spatio-temporal adaptive array processing in over-the-horizon radar (OTHR) and airborne radar applications in order to remove nonstationary multipath interference, known as “hot clutter”. Since the spatio-temporal properties of hot clutter cannot be assumed constant over the coherent processing interval (CPI), conventional adaptive techniques fail to provide effective hot-clutter mitigation without simultaneously degrading the properties of the backscattered radar signals, known as “cold clutter”. The approach presented incorporates multiple “stochastic” (data-dependent) constraints to achieve effective hot-clutter suppression, while maintaining distortionless output cold-clutter post-processing stationarity     

基于Hausdorff距离的反舰导弹目标选择方法

如何从舰艇编队中选择预定目标,是超视距反舰导弹亟待解决的一个问题。文章基于Hausdorff距离的部分匹配理论研究了这一问题。火控雷达探测到的编队信息和末制导雷达探测到的编队信息都用点集来描述,通过点集形状匹配获取这两个点集的对应点,从而实现对预定目标的选择。重点提出了一种新的部分匹配途径,能够自适应地逐个剔除引起形状不相似的外部点而同时保留两个形状的相似部分。仿真试验表明,相比以往基于编队相互位置关系的方法,论文所研究的预定目标选择方法具有更好的抗干扰能力。     

Commilitary-another new world order

The use of commercial practices to achieve military functional designs that provide high performance in inexpensive systems, designated here commilitary, is examined. Commilitary designs call for a mix of military quality and technology with some basic restrictions and approaches that are common to the commercial world. Areas such as parts selection, environmental conditions, levels of inspection and test, and configuration control which must be tailored for high volume modules are explored. A forward looking predictive windsheer radar is presented as a successful application of this approach     

超分辨距离-多普勒成像的动态优化方法

提出了超分辨距离多普勒成像的动态优化方法,基本思想是利用正则化图像重建方法及动态优化算法求出雷达目标反射率的最小二乘估计。还利用FFT大大提高了动态优化算法的计算效率。用B-52飞机缩比金属模型微波暗室转台实验数据和Boeing-727飞机外场实测数据进行成像的初步结果表明,采用超分辨成像方法可以获得更高的图像分辨力;或用较小的信号带宽和成像总转角,可以获得相同质量的图像。进一步研究发现,如果能充分利用成像区域中更多的先验信息,动态优化方法可望能提供更好的分辨性能。     

Space-time-frequency processing of synthetic aperture radar signals

The subject of this work is the detection and high resolution microwave imaging of objects moving on the ground and observed by an airborne radar. The proposed approach is based on a combined space-time and time-frequency processing. The space-time processing makes use of a linear array antenna and exploits the radar motion for filtering the received echoes in order to improve as much as possible the signal-to-disturbance ratio. The signal is then mapped onto the time-frequency domain, by computing its Wigner-Ville distribution, for a further filtering and for estimating its instantaneous frequency, necessary for the formation of a high resolution image of the moving object     

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     

A state-of-the-art review in radar polarimetry and its applicationsin remote sensing

The authors assess the state of the art, focusing on their own contributions. Covered areas are the electromagnetic inverse problem in radar polarimetry, coherent polarization radar theory, partially coherent polarization radar theory, vector (polarization) inverse scattering approaches, the polarimetric matched filter approach, polarimetric Doppler radar applications in meteorology and oceanography, and image fidelity in microwave vector diffraction tomographic imaging     

Multitarget detection using synthetic sampled aperture radars

A new multitarget detection technique using synthetic sampled aperture radar (SSAMAR) is presented. In contrast with the standard approach to multitarget detection, this technique may not require the use of phase shifting or tapering hardware. SSAMAR doubles the target pattern resolution, attenuates the sidelobes to about -27 dB, and significantly enhances the signal-to-noise ratio (SNR). Computer simulation is used to illustrate and validate this technique. Multitarget patterns for both standard and SSAMAR operations are provided     

Development of airborne moving target radar for long range surveillance

The following topics are discussed in the context of the development of an airborne moving target radar for long range surveillance: US Navy long range shipborne radar; Cadillac I airborne early warning (AEW) radar; Cadillac II airborne early warning (AEW) radar; airborne moving target indicating (AMTI) radar; related post-war radar activities; and the invention of the displaced center antenna. Among the topics studied is the use of a monopulse antenna in an MTI radar to remove the degradation of the MTI caused by rapid scanning of the antenna. A method of using a monopulse antenna for motion compensation in airborne MTI is discussed.<>     

Optimum Signals for Radar

The research reported herein deals with the general problem of the selection of radar waveforms. The investigation is specifically concerned with the synthesis of radar signals which are optimum in the sense that they are characterized by ambiguity surfaces minimized over certain predetermined regions of the ambiguity plane. The weighted ambiguity surface is utilized as the weighted error criterion. This error criterion is mathematically tractable and pertinent to radar system performance but is not unduly restrictive as some orientation parameters are left unspecified for subsequent cost or penalty function analysis. The signal optimization is approached by variational techniques augmented by equality and inequality constraints, for example, limiting the amount of bandwidth or frequency modulation to be less than some system requirement. Several examples are presented demonstrating the optimization techniques and providing a minimum error for the stated problem. It is shown that for any given type of amplitude modulation of the radar signal, the variance or dispersion of the ambiguity surface is not decreased for any type of phase modulation added. The optimum signal for an elliptical weighting function is derived for several cases. The minimum error is shown to depend upon the constraints and the unspecified orientation parameters and, for one case, on the second moment of the signal.