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     

On the performance of polarimetric target detection algorithms

The performance of six polarimetric target detection algorithms is analyzed. The detection performance of the optimal polarimetric detector (OPD), the identity-likelihood-ratio-test (ILRT), the polarimetric whitening filter (PWF), the single-polarimetric channel detector, the span detector, and the power maximization synthesis (PMS) detector is compared. Results are presented for both probabilistic and deterministic targets in the presence of complex Gaussian clutter. The results indicate that the PWF and the ILRT typically achieve near optimal performance. The remaining detection algorithms typically yield performance that is degraded compared to the performance of the OPD, the PWF, and the ILRT     

Studies of target detection algorithms that use polarimetric radardata

Algorithms are described which make use of polarimetric radar information in the detection and discrimination of targets in a ground clutter background. The optimal polarimetric detector (OPD) is derived. This algorithm processes the complete polarization scattering matrix (PSM) and provides the best possible detection performance from polarimetric radar data. Also derived is the best linear polarimetric detector, the polarimetric matched filter (PMF), and the structure of this detector is related to simple polarimetric target types. New polarimetric target and clutter models are described and used to predict the performance of the OPD and the PME. The performance of these algorithms is compared with that of simpler detectors that use only amplitude information to detect targets. The ability to discriminate between target types by exploring differences in polarimetric properties is discussed     

A real-time statistical polarimetric target model

A statistical approach to modeling and simulation of polarimetric electromagnetic fields backscattered from a reflecting body of a complex shape is described. A statistical scattering matrix is formulated and estimated for Rayleigh and Rician fluctuating (reciprocal and nonreciprocal) targets. The backscattered and received fields are modeled as a stochastic processes for arbitrary combination of transmit and receive polarization. A Monte Carlo simulation of a tank target is performed to verify the assumptions and approximations made and to demonstrate the feasibility of the real-time model. The results presented can be generalized to polarimetric clutter and to decoy modeling and simulation     

Adaptive polarimetric target detection with coherent radar. I.Detection against Gaussian background

The derivation of a completely adaptive polarimetric coherent scheme to detect a radar target against a Gaussian background is presented. A previously proposed Generalized Likelihood Ratio Test (GLRT) polarimetric detector is extended to the case of a general number of channels; this exploits the polarimetric characteristics of the received radar echoes to improve the detection performance. Together with the fully adaptive scheme, a model-based detector is derived that has a lower estimation loss. A complete theoretical expression is derived for the detection performance of both proposed polarimetric detectors. They are shown to have Constant False Alarm Rate (CFAR) when operating against Gaussian clutter, but to be sensitive to deviations from the Gaussian statistic. The application to recorded radar data demonstrates the performance improvement achievable in practice     

Adaptive polarimetric target detection with coherent radar. II.Detection against non-Gaussian background

For pt. I see ibid., vol. 37, no. 4, pp. 1194-1206 (2001).This paper presents the derivation of a polarimetric coherent adaptive scheme to detect a radar target against a non-Gaussian background. This completes the results presented in Part I for the Gaussian background. A Texture Free-Generalized Likelihood Ratio Test (TF-GLRT) detector is derived that exploits the polarimetric characteristics of the received radar echoes to improve the detection performance. The proposed polarimetric detector is shown to have Constant False Alarm Rate (CFAR) when operating against compound-Gaussian clutter with unknown parameters. Its performance is fully characterized by both theoretical analysis and simulation. Moreover, the application to recorded radar data demonstrates the performance improvement achievable in practice     

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     

Optimal speckle reduction in polarimetric SAR imagery

Speckle is a major cause of degradation in synthetic aperture radar (SAR) imagery. With the availability of fully polarimetric SAR data, it is possible to use the three complex elements (HH, HV, VV) of the polarimetric scattering matrix to reduce speckle. The optimal method for combining the elements of the scattering matrix to minimize image speckle is derived, and the solution is shown to be a polarimetric whitening filter (PWF). A simulation of spatially correlated, K-distributed, fully polarimetric clutter is then used to compare the PWF with other, suboptimal speckle-reduction methods. Target detection performance of the PWF, span, and single-channel |HH|² detectors is compared with that of the optimal polarimetric detector (OPD). A novel, constant-false-alarm-rate (CFAR) detector (the adaptive PWF) is as a simple alternative to the OPD for detecting targets in clutter. This algorithm estimates the polarization covariance of the clutter, uses the covariance to construct the minimum-speckle image, and then tests for the presence of a target. An exact theoretical analysis of the adaptive PWF is presented; the algorithm is shown to have detection performance comparable with that of the OPD     

Universal equations for radar target detection

Two equations express detection probability and detectability factor for all Swerling targets and for partially correlated intermediate cases.     

Clutter metrics for target detection systems

The problem of calculating an effective contrast for diffused targets in visual scenery is addressed. The effect of local variations of intensity in the vicinity of the target is modeled by considering the distribution of the intensity of the edges. The effect of global clutter is discussed from the vantage point of selecting the best model for background scenery. Generalized contrast measures are described and applied to real scenes     

Motion estimation for moving target detection

This paper describes a suite of techniques for the autonomous detection of moving targets by processing electro-optical sensor imagery (such as visible or infrared imagery). Specific application scenarios that require moving target detection capability are described, and solutions are developed under the constraints imposed by the scenarios. Performance evaluation results are presented using a test data set of over 300 images, consisting of real imagery (visible and infrared) representative of the application scenarios     

Optimal guidance for acceleration constrained missile andmaneuvering target

Explicit formulas of optimal guidance laws for an acceleration-constrained, arbitrary-order missile and maneuvering target are derived. These formulas are given in terms of the transfer function and acceleration constraint of the missile and the transfer function/shaping filter of the target. Optimal full-state feedback guidance law is synthesized against a target performing a barrel roll maneuver, and compared with the performance of proportional navigation (PN) for minimum and nonminimum phase missile. Simulation of a third-order missile shows the relative gain from using the full-order guidance law     

Rate-constrained target detection

Given little or no a priori information, a real world detection system has the task of allocating limited resources. Often these resources are themselves detection systems that operate at a slower rate, for example a tracker following a radar. Detection systems that are described by serial multiple decision points with each decision device assumed to be more reliable but slower than the device preceding it are considered. It is shown that because of the rate constraint the Neyman-Pearson criterion is suboptimum. An optimum rate-constraint test is developed which has the same likelihood ratio form as the Neyman-Pearson test. A strategy for controlling multiple-point detection sequences is developed that depends only on local information and is shown to be optimum under fairly broad conditions. The strategy can be implemented in practical systems, since it depends on the hit rate which is both controllable and observable. This approach to decision-making has applications in many fields and shows a promise as both an analysis and design tool     

Full-polarization matched-illumination for target detection and identification

This paper investigates the optimization of the full-polarization radar transmission waveform and the receiver response to maximize either target detection or identification performance. Application of such full-polarization matched-illumination techniques to simulated VHF-band frequency response data of mobile surface targets yields a significant performance improvement over that corresponding to chirped full-polarization transmission waveforms.     

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.     

A model for target detection with over-the-horizon radar

The effects of including Faraday rotation and multipath on the probability of detecting low-flying, distant, fluctuating and nonfluctuating targets immersed in Rayleigh noise plus clutter are studied. The effect of ionospheric fluctuations is also considered. It is found that both multipath and Faraday rotation strongly influence the detection statistics, with the effect being greatest for linearly polarized targets and less marked for symmetric targets     

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     

Optimal predictive sliding-mode guidance law for intercepting near-space hypersonic maneuvering target

The design of optimal guidance law for intercepting a near-space hypersonic maneuvering target with bounded inputs is considered. Firstly, a maneuvering model for near-space hypersonic aircraft is given. Then, the aircraft acceleration prediction can be obtained using this model with two neural networks. By using the target acceleration prediction, which is taken into account when calculating the Zero Effort Miss(ZEM), an optimal sliding-mode guidance law is proposed to fulfill the guidance task...     

A selection and estimation test for multiple target detection

The authors apply a selection and estimation procedure for the detection of multiple targets in clutter. The selection and estimation (SE) test performs better than a fixed order statistic (OS) detector. The SE test has some similarity to a variable trimmed mean (VTM) test and has a slight performance advantage. Unlike the VTM, whose performance is evaluated only by simulation studies, the performance of the SE test, for a Rayleigh fluctuating target model, can be evaluated analytically. Further improvement in the performance is possible if a better selection procedure can be found     

空间目标逆轨网捕拦截停泊轨道的优化设计

为了提高对空间目标的拦截成功率,可采用拦截器从停泊轨道转移进入拦截轨道逆轨网捕拦截的方式。利用椭圆弹道理论,讨论和分析了该拦截方式停泊轨道优化问题的描述、模型的建立及优化的方法。计算结果表明,对该拦截方式所建立的模型和采用的优化方法满足逆轨拦截对轨道设计的要求,可为空间快速拦截应用提供理论借鉴和参考。