NDLI: Multi-target trackers using cubature Kalman filter for Doppler radar tracking in clutter

Content Provider	IET Digital Library
Author	Roy, Anirban Mitra, Debjani
Abstract	A major feature of the Gaussian mixture probability hypothesis density (GM-PHD) filter is that it does not require any measurement-to-track association to complete its update step. This, according to the authors, should constitute significant advantage over conventional data-association based methods, especially in presence of high false-alarm rate, frequent miss-detections and targets in close proximity. To test this hypothesis, a multi-target tracking (MTT) problem using Doppler radar is considered, where the performance of GM-PHD algorithm is compared against six data-association based MTT filters in aforementioned adverse tracking conditions. To handle the non-linearity due to Doppler, cubature Kalman filter (CKF) is used in the framework of all MTT algorithms. Detailed mathematical framework of a new non-linear variant of GM-PHD using CKF has been derived using fundamental principles of non-linear Bayesian filtering. It is named as CK-GM-PHD. CK-GM-PHD is formulated using approximated Gaussian mixture assumption and follows track-oriented approach. Cubature integration method is used to numerically compute mean and covariance of components in the Gaussian mixture. Simulation results support the hypothesis by revealing substantial performance improvement of CK-GM-PHD algorithm over conventional data-association based approaches while tested in moderate to heavy clutter rate with lower detection probability and closely spaced target scenarios.
Starting Page	888
Ending Page	901
Page Count	14
ISSN	17519675
Volume Number	10
e-ISSN	17519683
Issue Number	Issue 8, Oct (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/10/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2015.0540
Journal	IET Signal Processing
Publisher Date	2016-05-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Approximated Gaussian Mixture Assumption Approximation Theory CKF Cubature Integration Method Cubature Kalman Filter Data-association Based MTT Filter Doppler Radar Doppler Radar Tracking Filtering Method in Signal Processing Gaussian Distribution Gaussian Mixture Probability Hypothesis Density Filter GM-PHD Filter Interpolation And Function Approximation Kalman Filter MTT Problem Multitarget Tracking Problem Nonlinear Bayesian Filtering Nonlinear Filter Numerical Analysis Radar Equipment Radar Tracking Statistics System And Application
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Extended target probability hypothesis density filter based on cubature Kalman filter

Cardinality balanced multitarget multi-Bernoulli filter for multipath multitarget tracking in over-the-horizon radar

Adaptive Gating for Multitarget Tracking With Gaussian Mixture Filters

Model-switched Gaussian sum cubature Kalman filter for attitude angle-aided three-dimensional target tracking

Novel N-scan GM-PHD-based approach for multi-target tracking

Extended GM-PHD filter for multitarget tracking in nonlinear/non-Gaussian system

Adaptive cardinality balanced multi-target multi-Bernoulli filter based on cubature Kalman

Improved multi-target tracking algorithm based on SMC-CBMeMBer for the airborne Doppler radar

Fifth-degree continuous–discrete cubature Kalman filter for radar

Multi-target trackers using cubature Kalman filter for Doppler radar tracking in clutter

Similar Documents

Extended target probability hypothesis density filter based on cubature Kalman filter

Cardinality balanced multitarget multi-Bernoulli filter for multipath multitarget tracking in over-the-horizon radar

Adaptive Gating for Multitarget Tracking With Gaussian Mixture Filters

Model-switched Gaussian sum cubature Kalman filter for attitude angle-aided three-dimensional target tracking

Novel N-scan GM-PHD-based approach for multi-target tracking

Extended GM-PHD filter for multitarget tracking in nonlinear/non-Gaussian system

Adaptive cardinality balanced multi-target multi-Bernoulli filter based on cubature Kalman

Improved multi-target tracking algorithm based on SMC-CBMeMBer for the airborne Doppler radar

Fifth-degree continuous–discrete cubature Kalman filter for radar

Multi-target trackers using cubature Kalman filter for Doppler radar tracking in clutter