An Adaptive Diagnose Scheme for Integrated Radar-Communication Antenna Array With Huge Noise

Smart sensors for wireless sensor networks are widely used on battlefields and in wild areas with poor natural conditions, where their antenna arrays are easily damaged and thus whose damage needs to be diagnosed in a timely manner via signal processing at an extremely low signal-to-noise ratio (SNR). This paper utilizes the fusion of the communication signal and the echos of probe signals received at the same antenna array, and it proposes a joint scheme for adaptive diagnose of the antenna. An iterative estimation scheme is implemented for the coupled problem of the estimation of the degree of arrival (DOA) and element damage patterns, and two confidence factors are proposed for a joint decision algorithm for evaluating the credibility of the estimation based on the two types of signals. The effectiveness of the proposed scheme is validated through simulation. The judgment error rate of the element damage patterns is reduced significantly under the joint scheme, for example, from 15% to only 3% for certain parameters. The gain of the joint decision algorithm is interpreted, and the optimal threshold of the confidence factors as well as the effect of the SNR of the communication and echo of the probe signals at the antenna element array are studied. This paper solves the problem of the diagnosis of antenna array elements at extremely low SNRs and will greatly contribute to the robust performance of smart sensors in wireless sensor networks.

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