Research On Coherent Radar Identification And Direction Of Arrival Technology Baced On Long Basedlines

In this paper, several key technologies of passive location are studied，which includecoherency identification of pulse signal and direction of arrival (DOA) estimation for bothbroadband and narrow-band signals based on long baselines.Based on the phase linearity of a pulse train, a coherency identification algorithm is proposedto deal with pulse signals. First of all, a sinusoidal sequence is created for the received pulsethrough coherent accumulation. The deviation of the phase difference between adjacent samplingpoints of the created sequence can be found. The number of phase transiton points can be gainedbased on a threshold. Then considering several elements, a secondary threshold can be set toidentify the coherency of the received pulse signal. A formula of minimum SNR needed ispresented. Simulation results show high performance of the proposed algorithm.A direction of arrival (DOA) estimation algorithm based on long baselines is proposed forhigh-accuracy direction-finding of broadband signals. The algorithm turns time differenceestimation into sinusoidal frequency estimation through time-frequency conversion. Thisalgorithm is able to get high performance of DOA estimation due to long baselines. Besides, theazimuth angle estimation and the pitch angle estimation for space objects are discussed.Simulation results show that the accuracy of the proposed algorithm can be close to the best underconventional SNR conditions.A long-baseline direction finding algorithm for narrowband signals is also discussed.Combining the signal arrival time estimation algorithm a DOA estimation algorithm fornarrowband signals based on long baselines is proposed. The unique set of phase ambiguitynumber can be acquired under some essential conditions. The algorithm gains high accuray ofdirection finding by extending the baseline length. The DOA estimation for multi-pulse signals isalso discussed. The correct rate of resolving phase ambiguity can be improved by rejecting thewild value with multiple measuring. The simulation results show the effectiveness of thealgorithm.