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Target range estimation based on a non-homogenous Poisson process model

Content Provider	IET Digital Library
Author	Yıldırım, Alper
Abstract	In this study, the author analyses target range estimation errors in matched filtering-based detection performed in high range resolution (HRR) radars. Conventional radar signal processors use point target detectors, where extended target responses are put through a point detection process by windowing and thresholding. The author demonstrates through simulations that the performance of degradation under the point target assumption can be significant for HRR radars, where targets extend across several detection cells. The author modelled the reflections for stationary and moving extended target scenarios by using three target signal models (TSMs). A non-homogenous Poisson process (NHPP) is provided to model the signal at the output of the target detector, which includes reflections from targets and clutter. The corresponding maximum likelihood (ML) estimator is derived as a range estimation technique. The author simulated a target detection process and made comparisons between the classical- and NHPP-based peak estimator performances for each of the TSMs. Furthermore, the ML estimation (MLE) algorithm is extended for multiple targets. The author demonstrates that the ML estimator significantly reduces target range estimation errors compared with the classical point target estimators.
Starting Page	249
Ending Page	258
Page Count	10
ISSN	17519675
Volume Number	7
e-ISSN	17519683
Issue Number	Issue 3, May (2013)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/7/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2011.0439
Journal	IET Signal Processing
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Classical Point Target Estimators Classical-based Peak Estimator Performances Clutter Conventional Radar Signal Processors Detection Cell Estimation Theory Filtering Method in Signal Processing Filtering Theory High Range Resolution Radars HRR Radars Matched Filtering-based Detection Maximum Likelihood Estimator ML Estimation Algorithm ML Estimator MLE Algorithm Moving Extended Target Scenario NHPP-based Peak Estimator Performances Nonhomogenous Poisson Process Model Point Detection Process Point Target Assumption Point Target Detector Radar Clutter Radar Detection Radar Equipment Radar Resolution Range Estimation Technique Signal Detection Stationary Extended Target Scenario Statistics System And Application Target Detection Process Target Range Estimation Error Target Responses Target Signal Model Target Tracking Thresholding Process TSM Windowing Process
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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