Superresolution HRR ATR with high definition vector imaging

A new 1-D template-based automatic target recognition (ATR) algorithm is developed and tested on high range resolution (HRR) profiles formed from synthetic aperture radar (SAR) images of targets taken from the Moving and Stationary Target Acquisition and Recognition (MSTAR) data set. In this work, a superresolution technique known as High Definition Vector Imaging (HDVI) is applied to the HRR profiles before the profiles are passed through ATR classification. The new I-D ATR system using HDVI demonstrates significantly improved target recognition compared with previous I-D ATR systems that use conventional image processing techniques. This improvement in target recognition is quantified by improvement in probability of correct classification (PCC). More importantly, the application of HDVI to HRR profiles helps to maintain the same ATR performance with reduced radar resource requirements     

CWLFM Radar for Ship Detection and Identification

Continuous wave lineal frequency modulated (CWLFM) radar presents some interesting advantages for coast surveillance and control as well as low probability of interception (LPI). This paper presents real results obtained with a radar prototype and processed with ISAR techniques. Also, results of an automatic ship identification system applied to simulated ISAR images are exposed. Moreover, radar behavior with unfavorable meteorological conditions is discussed     

Automatic stereo processing of high resolution radar imagery

Previously reported experiments with stereoscopic viewing of high resolution radar pictures demonstrated improvements in detection sensitivity up to 7 dB. This paper presents continued research into automatic algorithmic techniques for employing stereo information. A simple two-stage model for a human observer is proposed, and here we investigate the utility of an existing automatic stereo processor technique in application to radar imagery. It is shown that results obtained with the automatic processor very closely resemble those obtained through actual stereo viewing of radar pictures.     

Medium PRF set selection using evolutionary algorithms

This paper presents a new and novel method of selecting multiple pulse repetition frequency (PRF) sets for use in medium PRF pulsed-Doppler radars. Evolutionary algorithms are used to minimise the blind areas in the range/Doppler space. The evolutionary algorithm allows optimal solutions to be generated quickly, far faster than with exhaustive searches, and is fully automatic, unlike existing techniques. The evolved solutions compare very favorably against the results of both an exhaustive search and existing published PRF set selection methods. This evolutionary approach to generation of PRF sets is a major advance in medium PRF radar design.     

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.     

用VXI仪器组建通用雷达装备自动测试系统

武器装备的发展对测试系统提出了越来越高的要求。本文介绍了基于VXI总线卡式仪器和GPIB仪器组建的通用雷达装备自动测试系统的硬件结构，说明了测试软件的体系结构和设计方法。     

ADS-B用于高精度雷达标定的方法

为了更好地解决高精度雷达标定的问题,提出了基于广播式自动相关监视系统(ADS-B)固定误差及目标回波中心动态修正的雷达标定新方法。首先分析了ADS-B位置数据误差的来源、类型及在雷达坐标系下的特征,同时对民航目标回波中心的变化作了分析建模,在此基础上进一步通过对雷达数据与ADS-B数据之差作动态联合修正,最终估算出雷达系统误差,提高了雷达系统误差标定的精度和稳定性。并利用多批次的实测数据对该标定新方法与其他方法进行了对比验证,结果表明,该方法有效提高了标定的精度和稳定性,并已成功应用于雷达标定设备中。     

Dynamic Targets in CRRs Part II: Experiments and SAR Correspondence

Expressions describing the correspondence between moving-target artifacts for synthetic-aperture radar (SAR) and compact radar range (CRR) emulations are developed. Experimental results are then presented to verify the accuracy of these equations and to characterize the capacity of CRRs to emulate translating, vibrating, and rotating targets. We show that phase-compensation techniques can be applied to CRR data, providing a suitable test bed for SAR phase-compensation techniques.     

Differential GPS/inertial navigation approach/landing flight testresults

In November 1990, a differential GPS/inertial flight test was conducted to acquire a system performance database and demonstrate automatic landing using an integrated differential GPS/INS with barometric and radar altimeters. Flight test results obtained from postflight data analysis are presented. These results include characteristics of DGPS/inertial error, using a laser tracker as a reference. In addition, data are provided on the magnitude of the differential correlations and vertical channel performance with and without radar altimeter augmentation. Flight test results show one sigma DGPS/inertial horizontal errors of 9 ft and one sigma DGPS inertial vertical errors of 15 ft. Without selective availability effects, the differential corrections are less than 10 ft and are dominated by receiver unique errors over the time period of an approach. Therefore, the one sigma performance of the autonomous GPS (8-ft horizontal and 20-ft vertical) is very similar to the DGPS/inertial performance. Postprocessed results also demonstrate significant improvements in vertical channel performance when GPS/inertial is aided with radar altimeter along with a low-resolution terrain map     

雷达管制模拟练习绩效模糊综合评价研究

为了实现新一代雷达管制模拟机练习的自动评价,建立雷达管制模拟练习综合评价指标体系结构．运用层次分析法确定各个评价因素的权重系数,根据雷达管制练习中的要求建立评价因素的隶属函数。确定模糊综合评价模型,并运用模型对3名学员的雷达管制模拟练习进行了模糊综合评价。     

Over-the-horizon radar surveillance of airfields for counterdrugapplications

Airfield surveillance utilizing over-the-horizon radar (OTHR) offers the opportunity to gather significant intelligence concerning activity levels at suspect drug smuggling airports. It also provides the potential to classify aircraft initially from observed takeoff data, which would be helpful in interdiction efforts. This paper discusses the radar signal components and signal processing techniques required to accomplish this capability. An actual takeoff, observed by SRI International's Wide Aperture Research Facility (WARF), illustrates how the range-Doppler display plays an important role in developing and automating this capability. The ultimate capability is automatic takeoff recognition, initial target classification, rate of climb indication, and track to destination-all important contributions to the counterdrug command, control, and interdiction team     

Comparison of Two Target Classification Techniques

It has been shown that radar returns in the resonance region carry information regarding the overall dimensions and shape of targets. Two radar target classification techniques developed to utilize such returns are discussed. Both of these techniques utilize resonance region backscatter measurements of the radar cross section (RCS) and the intrinsic target backscattered phase. A target catalog used for testing the techniques was generated from measurements of the RCS of scale models of modern aircraft and naval ships using a radar range at The Ohio State University. To test the classification technique, targets had their RCS and phase taken from the data base and corrupted by errors to simulate full-scale propagation path and processing distortion. Several classification methods were then used to determine how well the corrupted measurements fit the measurement target signatures in the catalog. The first technique uses nearest neighbor (NN) algorithms on the RCS magnitude and (range corrected) phase at a number (e.g., 2, 4, or 8) of operating frequencies. The second technique uses an inverse Fourier transformation of the complex multifrequency radar returns to the time domain followed by cross correlation. Comparisons are made of the performance of the two techniques as a function of signal-to-error noise power ratio for various processing options.     

Automatic recognition of ISAR ship images

Inverse synthetic aperture radar (ISAR) produces images of ships at sea which human operators can be trained to recognize. Because ISAR uses the ship's own varying angular motions (roll, pitch, and yaw) for cross-range resolution, the viewing aspect and cross-range scale factor are continually changing on time scales of a few seconds. This and other characteristics of ISAR imaging make the problem of automatic recognition of ISAR images quite distinct from the recognition of optical images. The nature of ISAR imaging of ships, and single-frame and multiple-frame techniques for segmentation, feature extraction, and classification are described. Results are shown which illustrate a capability for automatic recognition of ISAR ship imagery     

Automatic target recognition using enhanced resolution SAR data

Using advanced technology, a new automatic target recognition (ATR) system has been developed that provides significantly improved target recognition performance compared with ATR systems that use conventional synthetic aperture radar (SAR) image-processing techniques. This significant improvement in target recognition performance is achieved by using a new superresolution image-processing technique that enhances SAR image resolution (and image quality) prior to performing target recognition. A computationally efficient two-level implementation of a template-based classifier is used to perform target recognition. The improvement in target recognition performance achieved using superresolution image processing in this new ATR system is quantified     

Efficient ATR using compression

We examine various model-based automatic target recognition (MBATR) classifiers to investigate the utility of model-catalog compression realized via signal-vector quantization (VQ) and feature extraction. We specifically investigate the impact of various compression rates and common automatic target recognition (ATR) scenario variations such as noise and occlusion through simulations on high-range resolution (HRR) radar and synthetic aperture radar (SAR) data. For this data, we show that significant computational savings are possible for modest decreases in classification performance.     

Detecting the Presence of Target Multiplicity

A method is discussed for detecting the presence of multiple targets in the radar antenna beam. It is assumed that the targets are unresolvable in range, Doppler, and angle using conventional monopulse resolution techniques. The basic approach taken is a generalization of the "quadrature" method, with significantly enhanced performance in the case when multiple pulses are integrated into a single solution. Detection and false alarm probabilities are derived analytically and the receiver operating characteristics are graphed. This study was performed for application to angle processing in a frequency agile automatic tracking radar, but the underlying concept is general and has applications outside this area.     

Threshold Control for Automatic Detection in Radar Systems

In automatic detection in radar systems an estimate of background clutter power is used to set the detection threshold. Usually detection cells surrounding the cell under test for the presence of a target are used to estimate the clutter power. In the research reported herein, the target location is taken to be uncertain and thus returns from a target could corrupt this clutter power estimate. It is shown how the threshold should be varied to compensate for the resulting degradation in detection performance. The threshold control procedure is based on a priori information about target location that could be supplied by the radar's tracking system. In addition, a simple procedure for calculating detection and false alarm probabilities for Swerling II target models is presented.     

Comments on "Angular Spectra in Radar Applications"

In [1], we proposed using "data adaptive" spectrum estimation techniques (e.g., maximum likelihood and maximum entropy) for radar problems such as separating low angle returns from ground reflections. W. White suggests [2] that these techniques will be of little value due to the correlation between the various received signals. In this rebuttal, we present additional conceptual arguments, simulation results and field data which support the utility of the techniques set forth in [1].     

基于自组织神经网络的软件功能测试数据自动生成

针对面向软件功能的测试数据自动生成问题,提出了一种动态自组织特征映射方法,用于生成揭示软件功能故障的测试数据(简称故障数据)。该方法主要有两部分组成,①采用具有全局多峰搜索特性的小生境遗传算法,在输入空间内搜索功能测试数据,生成少量的初始故障数据;②由初始故障数据,采用具有联想和分类能力的可变结构自组织特征映射,不断迭代生成大量相近而不同的故障数据,以便给开发者提供引发这些软件故障的信息,从而确定软件故障行为的模式或假设。用某型空空导弹发射控制软件进行了实验,运行结果表明了方法的有效性,故障数据生成效率高于遗传算法和随机法。