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Radar automatic target recognition (RATR) is an important function for modern radar. Target high resolution range profile (HRRP) contains target structure signatures, such as target size, scatterer distribution, etc., thereby radar HRRP target recognition has received intensive attention from the RATR community. Statistical modeling of target HRRPs is the key stage for HRRP statistical recognition,...
For spatial diversity multiple input multiple output (MIMO) radar, target echo signals received by its widely separated antennas may be semi-correlated and different in SNR. According to the correlation and SNRs of received target echo signals, a space partition based target detection method is proposed, which partition the surveillance volume into two sections, one using the coherent accumulating...
Radar high-resolution range profiles (HRRPs) are typical high-dimensional non-Gaussian and inter-dimensional dependently distributed data, the statistical modelling of which is a challenging task for HRRP based target recognition. Considering the inter-dimensional dependence, a recent work applied Factor Analysis (FA) to model radar HRRP data and showed promising recognition results, which however...
2-dimensional principal component analysis (2DPCA) has received more and more attentions in recent years, since it can evaluate the covariance matrix more accurate than PCA in extracting features from 2-dimensional images. However, a drawback of 2DPCA is that it needs more features than PCA because 2DPCA only eliminates the correlations between rows. In this paper, two-stage 2DPCA is proposed to extract...
A novel interferometric inverse synthetic aperture radar (InlSAR) imaging method, include an efficient phase unwrapping approach, is proposed, which can work very well under very low signal noise ratio condition. Based on which, an InlSAR image based target recognition method are proposed. The rotation and scale invariant features are extracted from the transformed InlSAR images, namely, the polar...
Radar automatic target recognition (ATR) based on multiple high range resolution profiles (HRRPs) is concerned. To relax the target aspect sensitivity and use more statistical information of the HRRPs, in this paper we extract the average range profile and the variance range profile together as the feature vectors for both training data and test data representation. And a decision rule is established...
Bispectra is widely used in the target recognition based on high resolution range profile (HRRP), but now using features generated from bispectra often need much storage and computation. In this paper, the low frequency part of bispectra is taken as the feature, then time domain processing and frequency domain processing are used to make the feature is more robust to the dimension change. Similarly...
A kernel optimization based on fusion kernel for HRRP is proposed in this paper. Based on the fusion of the 1-norm and 2-norm Gaussian kernels, our method combines the different characteristics of them so that not only is the kernel function optimized but also the speckle fluctuations of HRRP are restrained. Then on the radar measured data the presented method is employed to the kernel optimization...
Due to the aspect sensitivity of high-resolution range profile (HRRP), traditional radar HRRP target recognition methods usually use average profile within some target-aspect region as the target-aspect template. Actually, the amplitude fluctuation property of target HRRP also represents some feature information of the target. Based on the scattering center model, a new feature extraction method using...
Radar high-resolution range profile (HRRP) has received intensive attention from the radar automatic target recognition (RATR) community. Usually, complex HRRPs are not fully used for RATR but only their amplitude vectors, while the phase information of them is discarded due to the fact that the initial phase of a complex HRRP is strongly sensitive to target position variation. However, the phase...
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