文献类型：期刊文献

英文题名：A Specific Iterative Closest Point Algorithm for Estimating Radar System Errors

作者：Li, Pengfei[1];Fan, En[2];Yuan, Changhong[3]

机构：[1]Army Acad Artillery & Air Def Forces, Zhengzhou Campus, Zhengzhou 450052, Peoples R China;[2]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing 312000, Peoples R China;[3]Southern Med Univ, Network Ctr, Guangzhou 510515, Peoples R China

年份：2020

卷号：8

起止页码：6417

外文期刊名：IEEE ACCESS

收录：SCI-EXPANDED(收录号：WOS:000524682100054)、、EI(收录号：20200408078704)、Scopus(收录号：2-s2.0-85078240718)、WOS

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61703280, in part by the Zhejiang Natural Science Foundation under Grant LY20F020011, and in part by the International Science and Technology Corporation Base for Resource and Environment Informationization of Gansu Province.

语种：英文

外文关键词：Two-dimensional radar; ADS-B; ICP; system error registration; curve registration

外文摘要：A common radar system calibration approach is to use civil aviation automatic dependent surveillance-broadcast (ADS-B) data to register errors. Considering the temporal and spatial uncertainties in radar system observation data, a specific iterative closest point (SICP) algorithm is proposed for estimating two-dimensional (2D) radar system errors. Radar system errors consist of the measurement deviations for the slant range and azimuth of the target and are spatially reflected by the difference between the observed and actual (ADS-B-observed) positions of the same target. Thus, the SICP algorithm is used to register the tracks corresponding to radar and ADS-B observation data. The radar system errors are reflected by a translation, rather than a rotation, of the observation data. Therefore, in the SICP algorithm, a unit matrix first replaces the rotation matrix in the iterative closest point (ICP) algorithm. Then, the translation matrix is iteratively calculated, and finally, the cumulant of the translation matrix is calculated as the radar system error. The proposed algorithm is advantageous because it does not require the temporal registration of radar and ADS-B observation data when temporal and spatial uncertainties are present (e.g., when 2D radar observation data have low accuracy and contain many outliers). Additionally, the SICP algorithm can effectively reduce the dependence on sensor data accuracy. The experimental results obtained based on simulated and measured data demonstrate that compared to conventional registration algorithms, the proposed algorithm can rapidly and accurately estimate radar system errors and has higher registration accuracy.