{'fraction_non_alphanumeric': 0.017154389505549948, 'fraction_numerical': 0.0020181634712411706, 'mean_word_length': 5.358974358974359, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Spatial Detection of Passive Radar Signal in the Symmetrically Distributed Noise Field Based on Covariance Matrix Reduction

Radar working environment can be seen as a noise field which is approximately symmetrically distributed about the centre of the sensor array. In this work, a new signal detection method based on the imaginary part of covariance matrix (ICM) is proposed to achieve good signal detection. The real part of covariance matrix (RCM) was eliminated so as to suppress noise, and then the beam-forming was done by using only ICM. Choosing the beam output power as detection statistic, the Monte Carlo numerical method is used for signal detection in symmetrical noise environment. Simulation results show that the detector constructed using the proposed method can effectively suppress the strong noise, and achieve better signal detection capability than traditional method. The overall performance of the receiver operating characteristic (ROC) curve increases about 18dB.