Abstract
The acoustic signal of low-altitude aircraft shows regular distribution in frequency and has obvious harmonic crest of both fundamental frequency and double frequency.Therefore, this paper presents a low complexity algorithm of acoustic location based on feature sub-band extraction for low-altitude aircraft. The algorithm firstly searches the eigenfrequency points which occupy the main energy in the sound signal. Then the cost function is constructed based on the MUSIC method by the sub-band corresponding to the eigenfrequency point. Finally, the amplitude is weighted by the maximum ratio combination principle to obtain the spectral function of array space, by which DOA estimation is realized for the spatial spectrum. Simulation results show that the algorithm is less complex than traditional wide-band DOA algorithm, and its main lobe is easier to recognize and has better spatial resolution.
Highlights
With the continuous of unmanned aerial vehicle (UAV) technology, the safety problems caused by low-altitude aircraft, mainly composed of small UAVs become increasingly prominent[1].In the case of low altitude, the acoustic signal generated by the aircraft is accompanied with important information such as the position and the type of the aircraft, so the passive acoustic detection system has important research significance
The localization algorithm of this technology is mainly divided into three categories: acoustic source localization algorithm based on arrival delay[4], acoustic source localization algorithm based on high resolution spectrum estimation[5, 6] and acoustic source localization algorithm based
100 independent repeated experiments were conducted for each group with different SNR, and the DOA estimation error mean of traditional MUSIC algorithm and SE-MUSIC algorithm was recorded, and the relationship curve between DOA estimation error mean and SNR was depicted
Summary
With the continuous of unmanned aerial vehicle (UAV) technology, the safety problems caused by low-altitude aircraft, mainly composed of small UAVs become increasingly prominent[1].In the case of low altitude, the acoustic signal generated by the aircraft is accompanied with important information such as the position and the type of the aircraft, so the passive acoustic detection system has important research significance. Mainly refers to the use of acoustic signals for passive detection and the use of microphone array to estimate the DOA of sound source, known as spatial spectrum estimation. It has been highly valued in both military and civilian fields[2, 3].in order to realize sound source location, researchers have proposed many effective sound source location algorithms. Literature[9]proposed the Chicken swarm optimization based on MUSIC algorithm, which improves the accuracy of the algorithm. DOA estimation is carried out for some characteristic narrow-band signals, which greatly reduces the computation, and at the same time reduces the interference of partial invalid frequency components on DOA estimation in the case of low SNR, improving the accuracy and real-time performance of estimation
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