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Journal ArticleDOI

Exact theoretical performance analysis of optimum detector in statistical multi-input multi-output radars

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TLDR
After developing the optimum detector for a general case, exact closed-form expressions are derived for the probability of detection and false alarm as the derived expressions have complicated form, their interpretation is not tractable in the general case.
Abstract
This study is concerned with the performance analysis of detection problem in statistical multiple-input multiple-output radars for Gaussian interference. This subject has been addressed in some publications for such special cases as white Gaussian noise and orthogonal transmission. However, theoretical performance analysis of optimum detector for general case including coloured Gaussian interference and arbitrary transmission signal has not been reported yet. In the present study, after developing the optimum detector for a general case, exact closed-form expressions are derived for the probability of detection and false alarm. As the derived expressions have complicated form, their interpretation is not tractable in the general case. Therefore lower and upper Chernoff bounds are obtained to provide better insight into the detector performance. Furthermore, the effect of various parameters on the detector performance is investigated by Monte-Carlo simulations. Numerical analysis shows a high degree of consistency between the theoretical and Monte-Carlo simulation results.

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Citations
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Proceedings ArticleDOI

Design principles of MIMO radar detectors

TL;DR: A suitable detection structure is derived, and its performance is expressed in closed form as a function of the clutter statistical properties and of the space-time code matrix, in multiple-input multiple-output (MIMO) radars employing space- time coding (STC) to achieve diversity.
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Unified Optimization Framework for Multi-Static Radar Code Design Using Information-Theoretic Criteria

TL;DR: A discrete-time formulation of the problem as well as the optimal detector in the presence of Gaussian clutter are presented and two general methods based on Majorization-Minimization to tackle the optimization problems in the framework are proposed.
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Relative Entropy-Based Waveform Design for MIMO Radar Detection in the Presence of Clutter and Interference

TL;DR: An iterative method based on minorization-maximization (MM) technique to tackle the nonconvex design problem for multiple-input multiple-output (MIMO) radars and increases the design metric monotonically and is guaranteed to converge.
Journal ArticleDOI

Knowledge-based design of space–time transmit code and receive filter for a multiple-input–multiple-output radar in signal-dependent interference

TL;DR: The authors devise an iterative method which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR) and highlight the capability of the proposed method to robustify the performance of the designed system against possible knowledge inaccuracies.
Posted Content

Multichannel adaptive signal detection: Basic theory and literature review

TL;DR: In this article, a tutorial overview of multichannel adaptive signal detection, with emphasis on Gaussian background, is presented, and the main deign criteria for adaptive detectors, investigate the relationship between adaptive detection and filtering-then-CFAR detection, relationship between the adaptive detectors and adaptive filters, summarize typical adaptive detectors.
References
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Book

An Introduction to Signal Detection and Estimation

TL;DR: Signal Detection in Discrete Time and Signal Estimation in Continuous Time: Elements of Hypothesis Testing and Elements of Parameter Estimation.
Journal ArticleDOI

MIMO Radar with Colocated Antennas

TL;DR: It is shown that the waveform diversity offered by such a MIMO radar system enables significant superiority over its phased-array counterpart, including much improved parameter identifiability, direct applicability of adaptive techniques for parameter estimation, as well as superior flexibility of transmit beampattern designs.
Journal ArticleDOI

MIMO Radar with Widely Separated Antennas

TL;DR: It is shown that with noncoherent processing, a target's RCS spatial variations can be exploited to obtain a diversity gain for target detection and for estimation of various parameters, such as angle of arrival and Doppler.
Journal ArticleDOI

Spatial Diversity in Radars—Models and Detection Performance

TL;DR: The optimal detector in the Neyman–Pearson sense is developed and analyzed for the statistical MIMO radar and it is shown that the optimal detector consists of noncoherent processing of the receiver sensors' outputs and that for cases of practical interest, detection performance is superior to that obtained through coherent processing.
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