Proc. SPIE. 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018)
KEYWORDS: Signal to noise ratio, Principal component analysis, Detection and tracking algorithms, Sensors, Feature extraction, Signal processing, Target recognition, Electronic filtering, Defense technologies, Acoustics
Feature extraction based on Gammatone filterbank is more robust than that from Mel filterbank in underwater acoustic recognition. However, both conventional auditory features only represent the energy-based amplitude of the signal, and their performance decrease in low underwater SNR environments. Phase represented by instantaneous frequency (IF) may also contain some characteristics of the target. This paper proposes a novel fusion feature based on the outputs of Gammatone filters, in which an optimized algorithm of instantaneous frequency is given. Experiments employs Support Vector Machine (SVM) as the classifier and relative results indicate that significant performance gains can be obtained with instantaneous frequency information in low noise conditions.
Frequency-Modulated Continuous-Wave Synthetic Aperture Radar (FMCW SAR) is a promising compact remote imaging sensor. In this paper, a ground moving targets refocusing method is presented to provide FMCW SAR system with simultaneous moving targets indication application. This method is modified from range migration algorithm. To discriminate the target optimally, the concept of relative motion is utilized. The moving target is refocused like a fixed target. Its migrations both in the range and azimuth directions are completely compensated. Blind hypotheses of the relative velocities are used in the detection phase of moving targets. The step size between the hypotheses involves a trade-off between the computation load and detectability. In this paper, we determine the discretization based on the principle of stationary phase. The discretization reduces the computation burden and secures the detectability.