Adaptive Target Detector Research Articles

Subspace Detection for Range-Spread Target to Suppress Interference: Exploiting Persymmetry in Non-Homogeneous Scenario

This paper deals with subspace detection for range-spread target in non-homogeneous clutter with unknown covariance matrix where structured interference is presented in the received data. Through exploiting the persymmetry of the clutter covariance matrix, we propose two adaptive target detectors, which are referred to as persymmetric subspace Rao to suppress interference and persymmetric subspace Wald to suppress interference (“PS-Rao-I” and “PS-Wald-I”), respectively. The persymmetry-based design brings in the advantage of easy implementation for small training sample support. The signal flow analysis of the two detectors shows that the PS-Rao-I rejects interference and integrates signals successively through separated matrix projection, while the PS-Wald-I jointly achieves interference elimination and signal combination via oblique projection. In addition, both detectors are shown to be constant false alarm rate detectors, significantly improving the detection performance with other competing detectors under the condition of limited training.

Multi‐carrier and multi‐polarimetric model based adaptive target detector for passive radar systems

A new adaptive detection strategy for passive radar systems that fruitfully capitalizes on signals, simultaneously emitted by the same transmitter of opportunity at different carrier frequencies and collected by a set of differently polarized surveillance antennas is derived. Based on recent results that demonstrated the benefits provided by proper strategies to exploit polarimetric diversity, the authors aim at further improving the target detection performance by combining polarimetric and frequency diversity. Real data collected through an FM radio-based passive radar prototype is used to extensively demonstrate the effectiveness of the derived strategy with respect to state-of-the-art approaches. The conceived solution is proved to successfully enhance the capability to discriminate targets, thanks to an effective disturbance rejection performed at each frequency channel as well as a target echo enhancement and an increased robustness to the time-varying characteristics of the exploited source of opportunity.

Adaptive Target Detection in Passive Bistatic Radars: A Theoretical Analysis

This paper provides a theoretical analysis to consolidate the theory of “adaptive” target detection in the surveillance channel of passive bistatic radars where noise, strong returns of clutter and target returns are present. It is known in the literature that by generating the mixing product for each bistatic sample delay in the surveillance channel using the preprocessed and multipath-free reference channel signal, adaptivity can be realized. However, the theoretical background of this idea is not strong. In this paper, the statistical characteristics and the distribution of the mixing product are analyzed leading to the hypothesis test applicable to the “adaptive” detection problem. We investigate the iid requirements of secondary data, and a suitable scheme for secondary data generation in which these requirements are approximately satisfied is proposed. Several adaptive target detectors from active pulse radars’ literature based on the derived hypothesis test are generalized for use in passive radars and their performances are assessed by simulations and theoretical analysis. The simulation results indicate that these detectors are generally preferred compared to the conventional cross ambiguity function processing. It is also shown that the simulation-based and theoretical detection performances validate each other.

PERFORMANCE ANALYSIS OF A MODIFIED CFAR BASED RADAR DETECTOR UNDER PEARSON DISTRIBUTED CLUTTER

An adaptive target detector in radar system is used to extract targets from background in noisy environment of unknown statistics. The constant false alarm rate (CFAR) is well known detection algorithm that is being used in almost every modern radar. The cell averaging CFAR is the optimum detector in homogeneous clutter environment when the refence cells have identically independent and exponentially distributed signals. The performance of CA CFAR degrades seriously when clutter power substantially varies in non-homogeneous background. To overcome the performance degradation, a non-linear compression technique based CFAR has been introduced for adaptive thresholding to meet the challenges of target detection from various degrees of Pearson distributed non-homogeneous clutter. Extensive MATLAB simulations have been done using various levels of clutter input to show the effectiveness of the proposed design. Improvement in Signal-to-Noise ratio (SNR) has been achieved using Swerling I model for Rayleigh fluctuating target in the backdrop of heavy clutter.

Conjugate directions based order recursive implementation of post-Doppler adaptive target detectors

An implementation for the post-Doppler adaptive target detectors enabling an efficient change of the subspace dimension is described. The proposed implementation uses the order recursive structure of the conjugate directions method and does not present any additional computational burden on the processor. The implementation can be particularly useful for the adaptive detectors with an indeterminate number of auxiliary vectors for the clutter covariance matrix estimation. Through the proposed method, the subspace dimension can be easily increased or decreased according to the multiplicity of the auxiliary vectors at no loss of computational efficiency.