Simultaneous classification and ranging of direct fire weapons using an asynchronous acoustic sensor network

A direct fire weapon produces two impulsive sounds, namely, a muzzle blast and a ballistic shock wave, when firing a supersonic bullet. A ballistic model-based method which uses both the muzzle blast and shock wave received at each node of an asynchronous acoustic sensor network for simultaneous classification and ranging (SCR) of direct fire weapons is described. The initial speed and ballistic constant of the bullet are used as the classification features for the firing weapon, which are estimated using a nonlinear least-squares approach. A by-product of this classification feature estimation is an estimate of the detach point of the ballistic shock wave incident on each sensor node, from which the firing range relative to each node can be determined. The effectiveness of the proposed SCR method is demonstrated using both simulated and real data.