Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor
Abstract
:1. Introduction
2. Problem Formulation
2.1. Target Tracking Model
2.2. PCRLB of Target State
3. Novel Intercept Probability Factor
4. Multi-Sensor Scheduling Model
Algorithm 1 Multi-sensor scheduling algorithm |
Input: target state , sensor scheduling actions Output: sensor scheduling actions |
Determine whether the silent sensors have reached the silence time For (sensor in silent group) If (off-time> silence time) silent sensors start work else silent sensors keep silence End End Predict the IPF of sensors which do not keep silence For (sensor which don’t keep silence) IF (Predictive IPF > ) Sensor will be not selected and turn to silence End End Select the sensor-target combination which has the smallest PCRLB Use particle swarm optimization (PSO) algorithm to search the optimal scheduling actions Output sensor scheduling actions |
5. Solution Algorithm of Multi-Sensor Scheduling Problem
5.1. Solution Algorithm Based on Improved PSO Algorithm
5.2. Particle Encoding in Improved PSO Algorithm
Algorithm 2 Multi-sensor scheduling algorithm |
Input: illegal Output: legal |
For (each column of ) Sort elements in each column of the scheduling actions matrix from great to small. Select the previous elements and then change the element value to 1 Change the rest elements value to 0 End For (each row of ) Calculate the number of the elements whose value is 1 in each row If ( > ) Randomly select elements and then change the element value from 1 to 0 End End Output legal scheduling actions matrix |
6. Simulations
6.1. Scenario 1
6.2. Scenario 2
6.3. Scenario 3
7. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Xu, G.; Pang, C.; Duan, X.; Shan, G. Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor. Electronics 2019, 8, 140. https://doi.org/10.3390/electronics8020140
Xu G, Pang C, Duan X, Shan G. Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor. Electronics. 2019; 8(2):140. https://doi.org/10.3390/electronics8020140
Chicago/Turabian StyleXu, Gongguo, Ce Pang, Xiusheng Duan, and Ganlin Shan. 2019. "Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor" Electronics 8, no. 2: 140. https://doi.org/10.3390/electronics8020140
APA StyleXu, G., Pang, C., Duan, X., & Shan, G. (2019). Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor. Electronics, 8(2), 140. https://doi.org/10.3390/electronics8020140