Signal censoring and fusing with system‐level communication constraints in multistatic radar: a J‐divergence and Bhattacharyya distance‐based approach

Abstract

Decentralised detection using censored observations is an effective way to mitigate communication constraints where each sensor only transmits the ‘informative’ observations to a fusion centre (FC), and censors those deemed ‘uninformative’. In this study, a censoring rule is used at each spatial diversity channel such that only the observation exceeding a local threshold is transmitted, where the local threshold controls the communication rate. In particular, the authors consider a scenario where there exists a communication constraint at the FC. To design a proper communication bandwidth allocation (CBA) algorithm, two Ali‐Silvey distance measures, i.e. the J‐divergence (JD) and Bhattacharyya distance (BD), are utilised as objective functions to achieve a manageable optimisation procedure for designing local thresholds. The CBA algorithm is proposed by solving a constrained non‐linear programming problem through the sequential quadratic programming method. Besides, the detection performance is analysed under the censoring scheme, given the optimised local thresholds. Numerical results indicate that the two Ali‐Silvey distance‐based algorithms can outperform the uniform bandwidth allocation strategy; meanwhile, the BD‐based method performs better at high signal‐to‐noise scenarios but slightly worse at low, compared with the JD‐based method.

Keywords

• signal censoring
• signal fusing
• system‐level communication constraints
• multistatic radar
• J‐divergence
• Bhattacharyya distance