基于去相关无偏转换量测的外辐射源雷达跟踪算法OA

External radiation source passive radar,which detects targets by receiving signals from civilian trans-mitters,is valued for its strong stealth capabilities and low cost,playing a significant role in information warfare.Owing to the none-cooperative nature of the radiation source,the measurement errors are relatively large,necessitating the use of filtering technique to improve estimation accuracy.The converted measurement Kalman filter(CMKF)is a commonly used filtering technique for active radar.However,its application in passive radar is challenging due to the complex structure and high nonlinearity of converted measurement model.By improving multiple aspects such as state initializa-tion,state prediction and measurement conversion,a locally consistent unbiased converted measurement Kalman filter is designed for external radiation source passive radar.The filter employs higher-precision equivalent range and equivalent azimuth to characterize the target position during the converted measurement process.As a result,it demonstrates supe-rior accuracy and consistency under low signal-to-noise ratio(SNR)condition compared to canonical deterministic sam-pling algorithms,which indicates strong competitiveness of the proposed method.