Evolutionary Computational Intelligence-Based Multi-Objective Sensor Management for Multi-Target Tracking
In multi-sensor systems (MSSs), sensor selection is a critical technique for obtaining high-quality sensing data. However, when the number of sensors to be selected is unknown in advance, sensor selection is essentially non-deterministic polynomial-hard (NP-hard), and finding the optimal solution is...
Main Authors: | Shuang Liang, Yun Zhu, Hao Li, Junkun Yan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/14/15/3624 |
Similar Items
-
Multi-Objective Optimization Based Multi-Bernoulli Sensor Selection for Multi-Target Tracking
by: Yun Zhu, et al.
Published: (2019-02-01) -
An efficient multi-objective optimization approach for sensor management via multi-Bernoulli filtering
by: Yun Zhu, et al.
Published: (2022-07-01) -
Multi-Target Tracking by Associating and Fusing the Multi-Bernoulli Parameter Sets
by: Long Liu, et al.
Published: (2020-01-01) -
Multi-Sensor Multi-Target Tracking Using Probability Hypothesis Density Filter
by: Long Liu, et al.
Published: (2019-01-01) -
Sensor Selection for Decentralized Large-Scale Multi-Target Tracking Network
by: Feng Lian, et al.
Published: (2018-11-01)