MODELING GROUND VEHICLE ACOUSTIC SIGNATURES FOR ANALYSIS AND SYNTHESIS

Both security and weapon systems have used the wealth of information contained in acoustic sensor signals to reliably classify and identify moving ground vehicles. Developing robust signal processing algorithms that achieve these tasks is an expensive process, particularly in environments that include high levels of acoustic clutter or countermeasures that can generate false alarms. In this paper, the authors propose a parametric ground vehicle acoustic signature model to aid the system designer in understanding which signature features are important, developing corresponding feature extraction algorithms and generating low-cost, high-fidelity synthetic signatures for testing.The authors have proposed computergenerated acoustic signatures of certain armored, tracked ground vehicles to deceive acousticsensored smart munitions. They have developed quantitative measures of how accurately a synthetic acoustic signature matches those produced by actual vehicles in order to document synthetic signature performance and to evaluate proposed improvements. This paper describes the parameters of the model used to generate these synthetic signatures and suggests methods for extracting these parameters from signatures of valid vehicle encounters. The model incorporates wide-bandwidth and narrowbandwidth components that are modulated in a pseudo-random fashion to mimic the time dynamics of valid vehicle signatures. Narrowbandwidth feature extraction techniques estimate frequency, amplitude and phase information contained in a single set of narrow frequencyband harmonics. Wide-bandwidth feature extraction techniques estimate parameters of a correlated-noise-floor model. Finally, the authors propose a method of modeling the time dynamics of the harmonic amplitudes as a means of adding necessary time-varying features to the narrow-bandwidth signal components.The authors present results of applying this modeling technique to acoustic signatures recorded during encounters with one armored, tracked vehicle. Similar modeling techniques can be applied to security system applications in two areas: 1) understanding acoustic signature components that are important in particular applications and 2) developing low-cost, high fidelity acoustic signals for testing systems that avoid the cost of hiring high-value, ground vehicles for exhaustive testing.