Imaging altimeter (IALT) is a new type of radar altimeter system. In contrast to the conventional nadir-looking altimeters, such as HY-2A altimeter, Jason-1/2, and TOPEX/Poseidon, IALT observes the earth surface at low incident angles (2.5°–8°), so its swath is much wider and its spatial resolution is much higher than the previous altimeters. This paper presents a wind speed inversion method for the recently launched IALT onboard Tiangong-2 space station. Since the current calibration results of IALT do not agree well with the well-known wind geophysical model function at low incidence angles, a neural network is used to retrieve the ocean surface wind speed in this study. The wind speed inversion accuracy is evaluated by comparing with the ECMWF reanalysis wind speed, buoy wind speed, and in-situ ship measurements. The results show that the retrieved wind speed bias is about −0.21 m/s, and the root-mean-square (RMS) error is about 1.85 m/s. The wind speed accuracy of IALT meets the performance requirement.

成像高度计（IALT）是一种新型的雷达高度计系统。与HY-2A高度计，Jason-1 / 2和TOPEX / Poseidon等传统的最低点高度计不同，IALT在低入射角（2.5°–8°）观察地球表面，因此其覆盖范围很大更宽，其空间分辨率比以前的高度计高得多。本文介绍了天宫2号空间站上最近发射的IALT的风速反演方法。由于IALT的当前校准结果与低入射角下的众所周知的风地球物理模型函数不太吻合，因此在本研究中使用神经网络来检索海洋表面风速。通过与ECMWF再分析风速，浮标风速和原位比较，评估风速反演精度船舶尺寸。结果表明，检索到的风速偏差约为-0.21 m / s，均方根（RMS）误差约为1.85 m / s。IALT的风速精度满足性能要求。