We have studied the robustness of features against aspect variability for the purpose of target discrimination using polarimetric 35 Ghz ISAR data. Images at a resolution of 10 cm and 30 cm have been used for a complete aspect range of 360 degrees. The data covered four military targets: T72, ZSU23/4, T62, and BMP2. For the study we composed several feature vectors out of individual features extracted from the images. The features are divided into three categories: radiometric, geometric and polarimetric. We found that individual features show a strong variability as a function of aspect angle and cannot be used to discriminate between the targets irrespectively of the aspect angle. Using feature vectors and a maximum likelihood classifier reasonable discrimination (about 80%) between the four targets irrespective of the aspect angle was obtained at 10 cm resolution. At 30 cm resolution less significant discrimination (less than 70%) was found irrespective of the kind of feature vector used. In addition we investigated target discrimination per 30-degree aspect interval. In order to determine the aspect angle of targets we used a technique based on the Radon transformation, which gave an accuracy of about 5 degrees in aspect angle. We found that in this case good discrimination (more than 90%) was obtained at 10 cm resolution and reasonable discrimination (about 80%) at 30 cm resolution. The results are compared with analogous results from MSTAR data (30 cm resolution) of comparable targets.
The use of ISAR imagery for Automatic Target Recognition is seriously hampered by the difficulty of target motion compensation. Phase perturbations that result from target maneuvers during the processing interval need to be corrected for. In a previous paper, we demonstrated the use of the local Radon transform for estimating the radial velocity of a target. This estimate can then be used to align a sequence of range profiles prior to cross-range compression. In this paper, we make a quantitative comparison of the results that are obtained using different types of local Radon transformations. In the second part of this paper we outline an algorithm for compensation of phase perturbation that are caused by non-uniform target rotation. The algorithm has been tested on simulated data.
The use of the Radon transform and the Wigner-Radon power spectrum for ISAR motion compensation is described. It is shown that the local Radon power spectrum is closely related to the Cohen's class of quadratic time-frequency representations in a similar way as the Radon and Fourier transform are related. The peak of the local Radon transform is used as a measure for the velocity towards the radar of a moving target. The velocity estimate can be used to align the range profiles and perform target radial motion correction. Another application of the Radon transformation is the correction for time-variation of Doppler frequency of the signal during the Coherent Processing Interval. The Radon transform of the cross-range time-frequency representation of the signal is used for focusing an ISAR image that has been blurred due to non-uniform target rotation.