Projectile penetration positioning research based on microphone array

The rapid positioning of projectile penetration into steel target or concrete structure has been a hot topic in the field of explosion and impact. The traditional artificial target-marking system has the disadvantages of low safety factor, poor timeliness, large manpower consumption, poor precision and low efficiency, and it cannot meet the needs of launch test or training task in modern and information age. Optical measurement, such as high-speed video recording, is easy to be influenced by environment, and especially when there is the complex shooting range environment, the measurement data are easy to be influenced by weather, illumination and shooting range environment, etc. Furthermore, a large amount of dust and smoke produced from the explosion process can interfere with the projectile positioning accuracy. The remote sensing measurement method to identify the projectile penetration position have many problems, such as high cost, poor timeliness and low flexibility. In view of that, the acoustic positioning measurement method of projectile penetration process is proposed, which has the advantages of large monitoring range and being unaffected by visibility. A randomly arranged 16-channels transmitter array is used to receive sound pressure signals, and a digital acquisition device using corresponding audio interfaces is used to transmit the collected signal to a computer. A total of 5 seconds of audio signals are obtained and intercepted before and after the shell hits the target, and the signal is analyzed in time domain, frequency domain and time-frequency domain. Based on the conventional beamforming (CBF) algorithm and the CLEAN-SC algorithm, the projectile location during ignition, launch and penetration process is studied. The results showed that both the CBF and the CLEAN-SC algorithms can accurately locate the explosive position of gunpowder and the first impact position of the projectile on the target plate. What’s more, the results also showed that the accuracy of CLEAN-SC algorithm is better than that of CBF algorithm by contrasting the size of the main lobe.