Radar target identification using the bispectrum: a comparativestudy

Radar target identification is performed using time-domain bispectral features. The classification performance is compared with the performance of other classifiers that use either the impulse response or frequency domain response of the unknown target. The classification algorithms developed here are based on the spectral or the bispectral energy of the received backscatter signal. Classification results are obtained using simulated radar returns derived from measured scattering data from real radar targets. The performance of classifiers in the presence of additive Gaussian (colored or white), exponential noise, and Weibull noise are considered, along with cases where the azimuth position of the target is unknown. Finally, the effect on classification performance of responses horn extraneous point scatterers is investigated     

M-ary sequential hypothesis tests for automatic targetrecognition

Several forms of sequential hypothesis testing algorithms are described and their performance as classification algorithms for automatic target recognition is evaluated and compared. Several forms of parameteric algorithms, as well as a sequential form of a useful nonparametric algorithm are considered. The primary focus is the design of algorithms for automatic target recognition that produce maximally reliable decisions while requiring, on the average, a minimum number of backscatter measurements. The tradeoffs between the average number of required measurements and the error performance of the resulting algorithms are compared by means of Monte-Carlo simulation studies     

Radar target identification of aircraft using polarization-diversefeatures

The characteristics and target identification potential of a representation of the information from two polarization-diverse measurements of the radar backscatter of an unknown target are considered. The locus of these two polarization-diverse waveforms, termed the transient polarization response (TPR), has been shown to be closely related to the geometry of the scattering centers of the target. The polarization-related components of features derived from the TPR concur well with the shape and orientation of the major scattering centers distributed in the downrange profile of the object. This illustrates the intuitively appealing result that the polarization of the backscatter, as represented by the TPR and mapped onto the modified polarization chart, is determined by target geometry. It is shown that both polarization-related and amplitude-related features derived from the TPR are useful for target identification. By using distance measures that depend on various components, the elliptical parametrization information alone is sufficient to allow satisfactory target identification at SNRs of 0 dB and above. The significance of this result is that the absolute amplitudes of the received horizontally polarized and vertically polarized channels need not be known. However, if amplitude information is known, target identification percentages improve     

Modeling and performance of HF/OTH radar target classificationsystems

The effects of a class of multipath propagation channels on the performance of a over-the-horizon (OTH) radar target classification system are considered. A Rician frequency-selective fading channel model is employed to characterize the effects of the multipath propagation medium and evaluate the performance of radar target classification systems. The performance of classification algorithms that employ relative amplitude, relative phase, and absolute amplitude measurements as features is investigated. Performance estimates of the various classification algorithms for interesting sets of channel parameters are obtained by means of Monte-Carlo simulations