Research on Radar Emitter Identification Algorithm Based on Multi-Sensor Data Fusion

To improve the reliability and anti-jamming ability of the radar countermeasure reconnaissance system in the complex electromagnetic environment, we propose a multi-sensor data fusion algorithm for parameter estimation. Firstly, we eliminate abnormal data based on the quartile distribution plot method and obtain the mean and variance by batch estimation. Secondly, the consistency test is used to remove the sensor data with low support. After that, the inherent accuracy weights are determined based on the systematic errors of the sensors, the reliability weights are calculated by the adaptive fusion, and finally, the fusion results are obtained by weighting the batch estimation values with the combined weights of the two. Simulation experiments show that the proposed algorithm achieves excellent fusion adaptability, possesses better accuracy than the existing algorithms, and effectively improves the performance of multi-sensor radiation emitter identification.