Adaptive genetic MM-CPHD filter for multitarget tracking

Li, Bo; Zhao, Jianli; Pang, Fuwen

doi:10.1007/s00500-016-2087-0

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…In the two-dimensional (2D) surveillance region, we have in hand the state equation for mth (m = i, j) telerobot at time k [22][23][24][25][26] …”

Section: Problem Statementsmentioning

confidence: 99%

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Innovative sequential track-to-track algorithm for telerobots tracking based on heterogeneous sensors

Wang

2017

Advances in Mechanical Engineering

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In order to improve efficiency and accuracy of the existing telerobots tracking schemes, we present an innovative sequential track-to-track algorithm based on heterogeneous sensors in this article. Considering the effect of the difference of state estimation error on log-likelihood ratio, the modified sequential difference is first derived during the whole surveillance period. According to the chi-square test, the log-likelihood ratio under two hypotheses is further discussed using the weighted coefficient step by step. Subsequently, the extension for maneuvering telerobots tracking is derived based on the unscented Kalman filter. Finally, the numerical studies results indicate that the proposed sequential trackto-track algorithm has promising performance for tracking telerobots with various motion states.

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“…In the two-dimensional (2D) surveillance region, we have in hand the state equation for mth (m = i, j) telerobot at time k [22][23][24][25][26] …”

Section: Problem Statementsmentioning

confidence: 99%

“…To meet the needs of the chi-square test, we multiply À 2 with the proposed log-likelihood ratio between equations (23) and (25) and then get equation (22). Therefore, L( Dx ' 1 ' 2 ij (k)) can be regarded as a measure of relative support for one hypothesis against another for telerobots tracking.…”

Section: Principle Of the Proposed St2tamentioning

confidence: 99%

Innovative sequential track-to-track algorithm for telerobots tracking based on heterogeneous sensors

Wang

2017

Advances in Mechanical Engineering

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“…Recently, a new PCPHD filter was proposed based on the adaptive genetic method to boost estimation accuracy under the condition of the motion switching time. 17 In view of extended multi-target tracking, replacing traditional multi-measurement with a rectangular region of nonzero volume in the state space, a labeled box-PCPHD filter was presented in Zou et al, 18 which can propagate intensity function as well as cardinality distribution. In Lu et al, 19 a new PCPHD filter was proposed to complete efficient track continuity and extraction.…”

Section: Introductionmentioning

confidence: 99%

Innovative unscented transform–based particle cardinalized probability hypothesis density filter for multi-target tracking

2019

Measurement and Control

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Multi-target tracking is widely applied in video surveillance systems. As we know, although the standard particle cardinalized probability hypothesis density filter can estimate state of targets, it is difficult to define the proposal distribution function in prediction stage. Since the robust particles cannot be effectively drawn, the actual tracking accuracy should be enhanced. In this paper, an innovative unscented transform–based particle cardinalized probability hypothesis density filter is derived. Considering the different state spaces, we use the auxiliary particle method and then draw robust particles from the modified distributions in order to estimate the position of targets. Simultaneously, we present the recursion of the optimized Kalman gain to improve the general unscented transform for the velocity estimates. Using the track label, we further integrate them in the framework of the jump Markov model. The simulation results show that the proposed filter has advances in the multi-target tracking scenes. Moreover, the experiments indicate that the filter can track mobile targets with satisfactory results.

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State estimation of nonlinear dynamic system using novel heuristic filter based on genetic algorithm

Zandavi

Chung

2018

Soft Comput

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Adaptive genetic MM-CPHD filter for multitarget tracking

Cited by 3 publications

References 19 publications

Innovative sequential track-to-track algorithm for telerobots tracking based on heterogeneous sensors

Innovative sequential track-to-track algorithm for telerobots tracking based on heterogeneous sensors

Innovative unscented transform–based particle cardinalized probability hypothesis density filter for multi-target tracking

State estimation of nonlinear dynamic system using novel heuristic filter based on genetic algorithm

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