Using predicted target state to inform transmit waveform selection in active sonar

Abstract

Continuous-wave (CW) and frequency-modulated (FM) transmit pulses are commonly used in active sonar systems. CW pulses allow for measurement of target Doppler but have relatively poor range accuracy. In contrast, FM pulses are insensitive to Doppler but allow for improved range accuracy relative to CW. Active sonars often operate in clutter-dominated environments, where choosing a CW pulse for a high Doppler target provides better tracking capability, while an FM pulse is more effective for a low Doppler target. A challenge, however, is that the target Doppler not known before transmission. At present, the complementary strengths of CW and FM pulses can be exploited only by an operator who actively chooses between them, but requiring an operator to select the transmitted waveform on a ping-by-ping basis presents an unreasonable burden. In this talk, we describe the Predicted State-Based Selection (PSBS) algorithm, which uses an estimate of the target Doppler, derived from a state prediction produced by the tracking filter, to select the transmitted pulse. Monte Carlo simulations are conducted to evaluate the performance and behavior of the PSBS algorithm. Results show that PSBS improves target localization estimates by 7.7% on average relative to transmission of the same waveform for all pings.