2018
DOI: 10.3390/rs10060843
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Radar Target Recognition Using Salient Keypoint Descriptors and Multitask Sparse Representation

Abstract: Abstract:In this paper, we propose a novel approach to recognize radar targets on inverse synthetic aperture radar (ISAR) and synthetic aperture radar (SAR) images. This approach is based on the multiple salient keypoint descriptors (MSKD) and multitask sparse representation based classification (MSRC). Thus, to characterize the targets in the radar images, we combine the scale-invariant feature transform (SIFT) and the saliency map. The purpose of this combination is to reduce the number of SIFT keypoints by … Show more

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Cited by 27 publications
(23 citation statements)
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“…After extracting keypoints of SIFT, we will extract harbor candidates. It is a common method to use SIFT keypoints to match template images and target images [28], so we will use this method. Because the breakwaters of harbors are semi-closed and are also prominent in the sea, we use the breakwaters as the main keypoints of matching.…”
Section: Harbor Candidate Extractionmentioning
confidence: 99%
“…After extracting keypoints of SIFT, we will extract harbor candidates. It is a common method to use SIFT keypoints to match template images and target images [28], so we will use this method. Because the breakwaters of harbors are semi-closed and are also prominent in the sea, we use the breakwaters as the main keypoints of matching.…”
Section: Harbor Candidate Extractionmentioning
confidence: 99%
“…In this paper, the training dataset and test dataset are generated from the MSTAR dataset, provided by the Air Force Research Laboratory and the Defence Advanced Research Projects Agency (AFRL/DARPA) [4]. The dataset serves as a standard data set for the research of SAR ATR.…”
Section: Dataset Generationmentioning
confidence: 99%
“…Automatic target recognition (ATR) is the process of automatic target acquisition and classification, which is capable of recognizing targets or other objects, based on data obtained from the sensors, which has good application prospects in both military and civilian areas [3]. The process of SAR ATR can be summarized as finding regions of interest (ROIs) in the observed SAR image and classifying the category of each ROI (e.g., T72 or BTR70) [4]. Some earlier methods of SAR ATR can be found in [5][6][7][8][9].…”
Section: Introductionmentioning
confidence: 99%
“…If performing variable sampling or intensive sampling, then a more accurate signal can be obtained, but intensive sampling generates a lot of data. In data compression, signal and image feature extraction processing of other fields, they provide us some inspiration for processing MRS signals, such as synthetic aperture radar (SAR) images [27], penetrating radar noise filter [28], image processing [29] and so on. In particular, data compression and high-frequency sampling in SAR equipment provide us with exploring direction to process noisy MRS signal.…”
Section: Introductionmentioning
confidence: 99%