Data-Driven Joint Estimation for Blind Signal Based on GA-PSO Algorithm
LIU Shen1,2,3, QIN Yuannian1, LI Xiaofan2, ZHAO Yubin3, XU Chengzhong4
(1. Guilin University of Electronic Technology, Guilin, Guangxi 541004, China;
2. Shenzhen Institute of Radio Testing & Tech., Shenzhen, Guangdong 518000, China;
3. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518000,
4. University of Macau, Macau SAR 999078, China)
Without any prior information about related wireless transmitting nodes, joint estimation of the position and power of a blind signal combined with multiple co-frequency radio waves is a challenging task. Measuring the signal related data based on a group distributed sensor is an efficient way to infer the various characteristics of the signal sources. In this paper, we propose a particle swarm optimization to estimate multiple co-frequency “blind” source nodes, which is based on the received power data measured by the sensors. To distract the mix signals precisely, a genetic algorithm is applied, and it further improves the estimation performance of the system. The simulation results show the efficiency of the proposed algorithm.
Particle Swarm Optimization (PSO);Genetic Algorithm (GA);spatially distributed sensor;blind signal detection