Abstract : This paper introduces the use of dynamic features for robust target recognition of ground vehicles. Most current approaches rely on instantaneous spectral features such as those derived from harmonically related spectral lines. Significant drawback of these approaches are that the use of low amplitude (10-20dB below dominant line) spectral lines severely limit classification range. The strongest line is often detectable well before secondary lines. Dynamic features extracted directly from the strongest spectral line if successfully characterizing the target will extend the range of operation to several times. In this report a complete experimental evaluation of the effectiveness of dynamic features is conducted. The analysis is performed using a database consisting of approximately two hundred acoustic signatures collected from six unique vehicles. A number of features captured from the dynamic characteristic of the spectral line are evaluated. Classification performance is measured and presented in terms of confusion matrices. As an additional test of the classifier development tools developed for this task we selected added instantaneous spectral measurements to the dynamic feature and re-tested. We found that the performance of the classifiers using the mixed spectral and dynamic features was excellent but "blind" testing of the classifiers that were developed (testing against vehicle runs that were not used during classifier development) showed disappointing results.
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