The optimal energy allocation scheme for decision fusion in heterogeneous radar sensor networks

Information fusion for target detection in heterogeneous radar sensor networks (HRSN) is an attractive research area. By considering the heterogeneity of HRSN that different local radar sensors have different detection performances, we propose a decision fusion algorithm using optimized energy allocation in this paper. Simulation results show that compared with equal energy allocation scheme, the optimized energy allocation algorithm can provide better performance. Particularly, without the statistical knowledge of noise, we can get better performance via optimizing the energy allocation than equal energy allocation with the statistical knowledge of noise. In addition, we also propose a decision fusion algorithm for multi-target detection. Although the algorithm is optimum, it requires the statistical knowledge of noise. In order to reduce the requirement, an alternative fusion scheme, namely, approximate likelihood rate for multiple targets (ALR-MT) is proposed, which is equivalent to the optimum fusion rule at low SNR. Performance analysis is presented through simulation and theoretical calculation.