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Optimization of time and frequency resolution for radar transmitter identification

Optimization of time and frequency resolution for radar transmitter identification,10.1109/ICASSP.1999.756228,Bradford W. Gillespie,Les E. Atlas

Optimization of time and frequency resolution for radar transmitter identification   (Citations: 12)
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An entirely new set of criteria for the design of kernels for time-frequency representations (TFRs) has been previously proposed. The goal of these criteria is to produce kernels (and thus, TFRs) which will enable accurate classification without explicitly defining, a priori, the underlying structure that differentiates individual classes. These kernels, which are optimized to discriminate among multiple classes of signals, are referred to as signal class-dependent kernels, or simply class-dependent kernels. Until now, our technique has utilized the Rihaczek TFR as the base representation, deriving the optimal smoothing in time and frequency from this representation. Here the performance of the class-dependent approach is investigated in relation to the choice of the base representation. Classifier performance using several base TFRs is analyzed within the context of radar transmitter identification. It is shown that both the Rihaczek and the Wigner-Ville distributions yield equivalent results, far superior to the short-time Fourier transform. In addition, a correlation reduction step is presented. This improves performance and extensibility of the class-dependent approach
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    • ...Several classification prob­ lems involve non-stationary signals, such as radar transmit­ ter identification [1] and EEG classification problems...

    MARTHINUS C. DU PLESSISet al. Non-stationary signal classification using the undecimated wavelet pac...

    • ...Radar emitter recognition has attracted much attention in the last decade [1-5]...
    • ...Generally, these approaches can be divided into two categories: intentional modulation recognition [1] and unintentional modulation recognition [2-5]...
    • ...Ambiguity function (AF) was introduced to radar emitter recognition by Gillespie and Atlas in [2,3], where a class-dependent method was developed to optimize AF feature for classification and promising results have been achieved for simulation data from U.S...
    • ...Gillespie and Atlas proposed to use a class-dependent method [2,3] to classify radar emitters...
    • ...Similar to the class-dependent method in [2,3], our proposed algorithm evaluates the classification performance...
    • ...We should note that, although the class-dependent kernel optimization algorithm in [2,3] can achieve the same performance as our method (its performance curve is omitted), such whole plane optimization is only feasible for ideal radar data with short length or low sampling rate...
    • ...2) The class-dependent method in [2,3] is not applicable since the sampling points are relatively large for feature optimization in whole AF plane, resulting in the calculation and the store of higher order matrix...

    Lei Wanget al. Feature extraction and optimization of representative-slice in ambigui...

    • ...Time-frequency representation based approach for radar emitter identification has been proposed in [1]...

    Jarmo Lundenet al. Robust Estimation of Radar Pulse Modulation

    • ...Gillespie and Atlas [5] use the class-dependent time-frequency representations (TFRs) for radar transmitter...

    Lin Liet al. Specific radar emitter recognition based on wavelet packet transform a...

    • ...Time-frequency representation based approach for radar emitter identification has been proposed in [1]...

    Jarmo Lundenet al. Robust Estimation of Radar Pulse Modulation

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