Abstract:

Aimed at the impact of noise in receiving channels and signal distortion caused by sensors, simply improving the recognition performance of a single sensor no long meeting the demands, a collaborative representation based radar emitter fusion recognition of multisensor method is proposed. Firstly, a completed dictionary is constructed with offline sample signals in the training phase, on which collaborative coefficients of multiple receiving signals and classification residuals are obtained. Then, multisensor classification residuals and the D-S theory are combined by designing the basic probability assignment function reasonably, and consequently the fusion recognition result is acquired according to the maximum belief rule. Simulation experiments are performed by adopting 6 types of conventional radar emitters, the results validate the effectiveness of the proposed method and show that the method not only improves the performance in comparison with the single sensor, but is robust to noise and applicable to smallsamplesize recognition.