Abstract: The present disclosures discloses a method of target feature extraction based on millimeter-wave radar echo, which mainly solves the problems that techniques in the prior art cannot fully utilize raw radar echo information to obtain more separable features and cannot accurately distinguish targets with similar physical shapes and motion states. The method is implemented as follows: acquiring measured data of targets, generating an original RD map, and removing ground clutter of the map; sequentially performing target detection, clustering and centroid condensation on the RD map after the ground clutter removal; acquiring a continuous multi-frame RD maps and carrying out the target tracking; according to the tracking trajectory, selecting candidate areas and extracting features based on a single piece of RD map and features based on two successive RD maps, respectively.

Abstract: The present disclosures discloses a method of target feature extraction based on millimeter-wave radar echo, which mainly solves the problems that techniques in the prior art cannot fully utilize raw radar echo information to obtain more separable features and cannot accurately distinguish targets with similar physical shapes and motion states. The method is implemented as follows: acquiring measured data of targets, generating an original RD map, and removing ground clutter of the map; sequentially performing target detection, clustering and centroid condensation on the RD map after the ground clutter removal; acquiring a continuous multi-frame RD maps and carrying out the target tracking; according to the tracking trajectory, selecting candidate areas and extracting features based on a single piece of RD map and features based on two successive RD maps, respectively.

Abstract: Automated methods and systems are provided for presenting and scoring items which are presented in different question formats that include graphics interpretation, two-part analysis, table analysis, and multi-source reasoning. There are a plurality of response opportunities for each item, and each response opportunity is independent of each other. In operation, an item is presented in the respective question format on a processor-controlled user interface display screen. A response engine receives the response for each response opportunity. A scoring engine in communication with the response engine receives the plurality of responses and scores the plurality of responses by determining whether the response selected for each response opportunity is correct, and assigning credit for the item only if each of the responses for each of the response opportunities is correct, and assigning no credit for the item if at least one of the responses for each of the response opportunities is incorrect.

Abstract: Automated methods and systems are provided for presenting and scoring items which are presented in different question formats that include graphics interpretation, two-part analysis, table analysis, and multi-source reasoning. There are a plurality of response opportunities for each item, and each response opportunity is independent of each other. In operation, an item is presented in the respective question format on a processor-controlled user interface display screen. A response engine receives the response for each response opportunity. A scoring engine in communication with the response engine receives the plurality of responses and scores the plurality of responses by determining whether the response selected for each response opportunity is correct, and assigning credit for the item only if each of the responses for each of the response opportunities is correct, and assigning no credit for the item if at least one of the responses for each of the response opportunities is incorrect.