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The Neyman-Pearson detector can be approximated by MultiLayer Perceptrons (MLPs) trained in a supervised way to minimize the Mean Square Error. The detection of a known target in a Weibull-distributed clutter and white Gaussian noise is considered. Because of the difficulty to obtain analytical expressions for the optimum detector under this environment, a suboptimum detector like the Target Sequence...
We present a double-parameter CFAR with very reasonable losses and low computational complexity. Its basic architecture has been conceived from tail extrapolation theory. The detector uses a detection threshold, set from the measured PFA which is obtained with an auxiliary threshold (pseudothreshold), lower than the final detection threshold. Starting from the basic scheme, a CFAR detector for Weibull...
We work on the task of 2D articulated human pose tracking in monocular image sequences, an extremely challenging task due to background cluttering, variation in body appearance, occlusion and imaging conditions. Most of current approaches only deal with simple appearance and body part dependencies, especially the Gaussian tree-structured priors assumed over body part connections. Such prior...
To detect the transport of nuclear and conventional Weapons of Mass Destruction and other bulk contraband, Decision Sciences International Corporation (DSIC) created the Multi-Mode Passive Detection System (MMPDS), capable of imaging the contents of cargo containers and vehicles without applying ionizing radiation. A reconstructed image volume of the detector space is generated from the detector measurements...
Classical space-time adaptive processing (STAP) detectors are strongly limited when fadng highly heterogeneous environments. Indeed, in this case, representative target free data are no longer available. Single dataset algorithms such as the MLED algorithm, have proved their efficiency in overcoming this problem by only working on primary data. These methods are based on the APES algorithm which removes...
The paper addresses the problem of target detection embedded in a disturbance composed of a low rank Gaussian clutter and a white Gaussian noise. In this context, it is interesting to use an adaptive version of the Low Rank Normalized Matched Filter detector, denoted LR-ANMF, which is a function of the estimation of the projector onto the clutter subspace. In this paper, we show that the LR-ANMF detector...
In this paper we present a modified version of a previously proposed anomaly detector for polarimetric imagery. This modified version is a more adaptive, range invariant anomaly detector based on the covariance difference test, the M-Box. The paper demonstrates the underlying issue of range to target dependency of the previous algorithm and offers a solution that is very easily implemented with the...
In 1950 Abraham Wald proved that every admissible statistical decision rule is either a Bayesian procedure or the limit of a sequence of such procedures. He thus provided a decision-theoretic justification for the use of Bayesian inference, even for non-Bayesian problems. It is often assumed that his result also justified the use of Bayesian priors to solve such problems. However, the principles one...
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...
This paper proposes a novel distributed multiple-input and multiple-output (MIMO) phased radar with orthogonal frequency-division multiplexing (OFDM) waveform, i.e., OFDM-MIMO phased radar system, to improve the detection performance of high speed moving target with radar cross-section (RCS) fluctuation. The parallel incoherent processing of the spatial diversity multi-channel echoes data in a short...
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...
Ship detection is an important topic for security and surveillance of maritime and costal areas. A solution exploiting satellite-borne SAR sensors is particularly interesting, because it offers wide scale surveillance capabilities, which are not reliant on solar illumination and are rather independent of weather conditions ([1], [2], [3]). In SAR images, the main feature of a ship is a relatively...
In this paper, a new adaptive and fast Constant false alarm rate (CFAR) target detection algorithm based on two level CFAR (TL-CFAR) detectors in high-resolution synthetic aperture radar (SAR) images is proposed. In the first level, the initial mask of targets is obtained by Cell Averaging CFAR (CA-CFAR) detector. In the second level, the precise parameters estimation of CFAR in the local window is...
The Variability Index Modified Rank Squared (VIMRS) nonparametric detector is introduced in this article. Depending on whether the background environment is homogeneous or not, VI-MRS can select Modified Rank Squared CFAR (MRS-CFAR), Greatest of Modified Rank Squared CFAR (GO-MRS-CFAR), or Trimmed Modified Rank Squared CFAR (TMRS-CFAR) to compute the threshold adaptively. The performance of the proposed...
Introduced to the hyperspectral imaging community in the WHISPERS 2010 Reykjavik meeting, the “clairvoyant fusion” methodology for creating detection algorithms has since been applied to a variety of binary decision problems. These are summarized here. For any detection problem amenable to a fusion approach, an infinity of “flavors” can be devised. This paper describes what problems have been formulated...
We present the problem of moving target detection with multiple-input multiple-output (MIMO) radar in compound-Gaussian clutter. A new moving target detector based on the Wald criterion is devised according to the centralized processing scheme of MIMO radar system. Furthermore, the adaptive version of the proposed detector is investigated by in place of the exact covariance matrix with the fixed point...
This paper considers moving target detection for multiple-input multiple-output (MIMO) radar in compound-Gaussian clutter. A new detector is devised according to a centralized processing scheme for MIMO radar system based on the generalized likelihood ratio test (GLRT) design criterion. Then, an adaptive version of the derived detector is investigated. The fixed point estimation (FPE) strategy is...
This paper examines target detection using a Linear Support Vector Machine (L-SVM). Traditional radars typically use a Constant False Alarm Rate (CFAR) processor to adaptively adjust the detection threshold based on the fast-time return signal. The SVM formulation uses the same block-diagram structure as the CFAR approach; however, data from the leading and lagging windows is directly used to classify...
The compound-Gaussian (CG) distribution with the inverse Gaussian (IG) texture is represented as the IG-CG distribution and validated to provide the better fit with the recorded clutter data than the traditional K distribution as well as the complex multivariate t distribution. In this paper, the adaptive detector of multiple-input multiple-output (MIMO) radar is firstly proposed in terms of the generalized...
This paper considers the moving target detection (MTD) problem for polarimetric multiple-input multiple-output (MIMO) radar in the presence of Gaussian clutter. By exploiting the polarimetric information, we devise two different generalized likelihood ratio tests (GLRTs) with a generic number of polarimetric channels, according to the centralized and distributed processing schemes of MIMO radar systems,...
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