Shiwen Lei

A CFAR Adaptive Subspace Detector Based on a Single Observation in System-Dependent Clutter Background

In this paper, the problem of detecting target in system-dependent clutter (SDC) background with a single observation from the test cell is researched. Classical detectors, such as the generalized likelihood ratio detectors (GLRDs) and the adaptive matched filters (AMFs), etc., usually deal with the clutter and the noise as a whole. The low rank detectors (LRDs) make use of the low rank property of the clutter to improve the detection performance. However, the performance of LRDs degrades when the signal is not orthogonal with respect to (w.r.t.) the clutter. In this paper, an adaptive subspace detector for SDC (SDC-ASD) background which deals with the clutter and the noise separately is proposed. The SDC-ASD designs the test statistic by replacing the signal and the clutter covariance matrix with their maximum likelihood estimations (MLEs). Its theoretical false alarm probability and detection probability are analytically deduced. Analytical results show that the test statistic has the form of non-central F distribution. Besides, it is shown that the SDC-ASD has constant false alarm rate (CFAR) performance w.r.t. the clutter and the noise. Numerical experiments are provided to validate the detection performance of the SDC-ASD in dealing with the target detection in SDC background.

Adaptive polarimetric detection method for target in partially homogeneous background

In this paper, the problem of enhancing the detection performance of detector for target in partially homogeneous background is addressed. Based on a general measurement model, a new constant false alarm rate (CFAR) adaptive matched detector (AMD) is proposed through a two-step design procedure. The detection performance of the AMD is theoretically analyzed. Then, the correctness of the analytical results and the effectiveness of the AMD are validated through numerical experiments and IPIX radar data. To further improve the detection performance of AMD, optimal polarimetric waveform design is approached. The waveform is designed by optimally selecting the transmitted polarization that maximizes a non-central parameter of the detection probability. Numerical experiments are provided to validate the performance improvement by comparing the optimal AMD with the optimal adaptive subspace detector (ASD) and the fixed AMDs. Comparison results show that a gain of 1-5dB is obtained by the optimal AMD. HighlightsThis paper researches the target detection problem in partially homogeneous background.A CFAR adaptive matched detector (AMD) is proposed to improve the detection performance.The theoretical analyses of the AMD prove that the AMD is high efficiency and can be adapted to a wider target detection filed.The optimal polarimetric waveform design scheme based on the AMD is addressed which improves the detection performance.

An adaptive subspace detector for target in target-induced clutter plus Gaussian noise background

In this paper, we consider the problem of detecting target in target-induced clutter (TIC) plus Gaussian noise background. Processing this detection problem, the traditional generalized likelihood ratio detector (GLRD) deals with the clutter as a part of the noise. An adaptive subspace detector for TIC (TIC-ASD) background is proposed. Different from the traditional GLRD, the TIC-ASD deals with the clutter and the noise separately. The signal and the clutter covariance matrix are estimated with the aid of generalized likelihood ratio (GLR) principle. The test statistic is constructed by replacing the signal and the clutter covariance matrix with their maximum likelihood estimations (MLEs). Experimental simulations are provided to demonstrate the detection performance of the TIC-ASD and the GLRD. Simulation results show that the TIC-ASD outperforms the GLRD in both single antenna and multi antenna scenarios.

An adaptive detector for detecting target in clutter plus Gaussian noise background

In this paper, the problem of target detection in the clutter plus Gaussian noise background is considered. The published detectors group the clutter and the noise as a single parameter; differently, we deal separately with the clutter and the noise. In the paper, the noise is assumed to be obtained in advance and the clutter is distributed according to a certain distribution. An adaptive target detector which utilizes the maximum likelihood estimate (MLE) of the clutter covariance and the MLE of the signal of interest (SOI) is proposed. The detector has a simpler expression than the published detectors. To validate its detection performance, the proposed detector is compared with three published detectors. Numerical experimental results demonstrate that the proposed detector has better detection performance; moreover, the proposed detector can obtain reliable detection performance with less secondary data.

A new time-of-flight (TOF) picker for tumor tissue in microwave induced thermo-acoustic tomography (MITAT) system

In this paper, a new method for accurately picking the time-of-flights (TOFs) of tumor is proposed in microwave induced thermo-acoustic tomography (MITAT) system. The proposed method makes use of the properties of induced thermal acoustic signal and combines them with the wavelet transform and Akaike information criterion (AIC). Both numerical simulations and ex vivo experimental results are given to test the performance of the proposed method. Through the simulations and experiment, the proposed method can efficiently and accurately pick the TOFs of tumor target in MITAT system and therefore provide a guarantee for imaging tumor with high accuracy.

Effects of frequency information to the electromagnetic inverse scattering series method (EISSM)

For subsurface sensing objects using electromagnetic waves, most of current imaging methods need priori information of exact dielectric properties of background media in order to accurately reconstruct the concealed targets. This condition is hardly satisfied in practice. Recently, an efficiently qualitative imaging method termed electromagnetic inverse scattering series method (EISSM) is developed to image the buried targets. EISSM reconstructs concealed targets in the layered media by only utilizing dielectric properties of free space. However, the effects of frequency information to the EISSM have never been discussed. In this paper, we analyze and discuss the effects of frequency information to the performance of EISSM when imaging the buried objects. Through some numerical simulations, EISSM can obtain favorable image results with a broad frequency spectrum of measured data.

Fast optimization method of polarization receiving power for monostatic condition based on Kennaugh matrix

Different polarization incidences and/or inflections yield different polarization scattering powers. The problem of searching optimal polarization state for the maximal polarization receiving power (PRP) is of significantly meaningful. Usually, there are no analytic solutions to the problem and current numerical methods are time consuming. Aiming to reduce the computational time, fast optimization mechanism is studied in this paper. An improved Lagrange method (ILM) based on bisection strategy is proposed for monostatic condition. This method takes the advantage of monotonicity of a cost function constructed by Lagrange multiplier to accelerate searching speed. The performance of this method is validated by comparing with the Lagrange method proposed by Chen (LMC). Numerical experiments demonstrate that the proposed method in this paper is superior to the existing method.

Polarization optimization in clutter background via target scattering estimation

The problem of designing the states of polarization (SOPs) of the transmitter and receiver in clutter background via target scattering estimation is discussed. Under the assumption that the covariance of the clutter and noise is known a prior, the Cramer-Rao lower bound (CRLB) for the mean square error (MSE) of estimating the target is deduced. The problem of the minimizing MSE is converted to be a constrained optimization one. The paper solves this constrained optimization problem to optimally design the SOPs of the transmitter and the receiver. The performance of the proposed method is compared with conventional ones. Numerical results indicate that a significant amount of power gain is achieved in the target scattering estimation with the proposed method.

Fast optimization method for polarization receiving based on space mapping theory

Aiming to solve the optimization problem of radar polarimetry, a fast local search method (FLSM) is proposed for bistatic case. The FLSM expedites searching speed of the optimal polarization by restricting the optimal solution in a local area. This local area is defined by the polarization states with respect to the maximum and minimum polarization receiving power (PRP). The performance of the FLSM is validated by comparing with the three-step method (TSM). Theoretical analyses indicate that the FLSM obtains the optimal PRP by searching an area which, statistically, has less than 25.26% searching area of the TSM. Numerical experiments demonstrate that the proposed method obtains the optimal polarization states more quickly and effectively than the TSM.