一种新的雷达HRRP自适应划分角域建模方法

基于雷达方位渐变高分辨距离像(HRRP)的连续性，提出了一种自适应递归划分角域的建模方法，利用自适应高斯分类器和高斯过程分类器，从雷达数据中提取连续HRRP序列中包含的非线性结构信息；提出了一种判定角域边界的准则，递归地对雷达数据自适应划分角域．实测数据仿真试验证明了该方法优于传统的等间隔划分角域建模法．

New adaptive angular-sector segmentation algorithm for radar ATR based on HRRP

In the field of high resolution range profile (HRRP) based radar automatic target recognition (ATR), it is an effective approach to tackle the target-aspect sensitivity by segmenting continuous radar data into several sectors in equal angular intervals. This equal angular-sector segmentation algorithm is based on the condition for good quality of ISAR images, but it is not a satisfactory choice with the application of ATR for its inclination to cause model mismatch, performance limitation, and time-consumption. This paper proposes a recursive algorithm for adaptively angular sector segmenting based on Adaptive Gaussian Classifier (AGC) and Gaussian Processes classifier (GPC).Since the HRRP data are continuous along the azimuth,we first exploit the nonlinear structure characteristic embedded in HRRP data through AGC or GPC, then present a criterion for determining the angular-sector boundary, and finally recursively segment the data. Promising experimental results are presented for measured radar data.