NDLI: Joint detection and tracking of non-ellipsoidal extended targets based on cubature Kalman-CBMeMBer sub-random matrices filter

Content Provider	IET Digital Library
Author	Barbary, Mohamed ElAzeem, Mohamed H. Abd
Abstract	Joint detection and tracking of multiple extended targets (ETs) from image observations is a challenging radar technology; especially for extended stealth targets (ESTs). This work provides a new approach for the ESTs tracking under the non-linear Gaussian system based on track-before-detect (TBD) approach. The sequential Monte Carlo cardinality-balanced multi-target multi-Bernoulli (SMC-CBMeMBer) filter provides a good framework to cope with TBD approach. However, this filter suffers from the particles’ degradation problem seriously; especially for ETs tracking. Recently, the cubature Kalman (CK)-CBMeMBer filter which employs a third-degree spherical-radical cubature rule has been proposed to handle the non-linear models, the CK-CBMeMBer filter is more accurate and more principled in mathematical terms compared to SMC-CBMeMBer filter. To this point, the authors address a TBD of ESTs with extended CK-CBMeMBer filter based on random matrix model (RMM), which is an efficient way to track ellipsoidal ESTs. In RMM-ESTs scenarios, although the extension ellipsoid is efficient, it may not be accurate enough because of lacking useful information, such as size, shape, and orientation. Therefore, they introduce a filter composed of sub-ellipses; each one is represented by a RMM. The results confirm the effectiveness and robustness of the proposed filter.
Starting Page	4676
Ending Page	4689
Page Count	14
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 17, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.1181
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/17
Journal	IET Image Processing
Publisher Date	2021-01-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Challenging Radar Technology Cubature Kalman-CBMeMBer Filter Cubature Kalman-CBMeMBer Sub-random Matrices Filter Ellipsoidal ESTs ESTs Tracking ETs Tracking Extended CK-CBMeMBer Filter Extended Stealth Targets Filtering Method in Signal Processing Filtering Theory Kalman Filter Matrix Algebra Monte Carlo Method Multiple Extended Targets Nonellipsoidal Extended Targets Nonlinear Gaussian System Nonlinear Model Radar Detection Radar Equipment Radar Tracking Random Matrix Model Random Processes RMM-ESTs Scenario Sequential Monte Carlo Cardinality-balanced Multitarget MultiBernoulli Filter SMC-CBMeMBer Filter System And Application Target Tracking TBD Approach Third-degree Spherical-radical Cubature Rule Track-before-detect Approach Tracking Filter
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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