基于功率最小熵的毫米波交通雷达误差校准方法

交通雷达利用多输入多输出(MIMO)技术达到以较小自由度获取高角度分辨率的目的,然而,由于高集成度硬件加工工艺及器件老化等因素限制,毫米波MIMO雷达各通道间存在幅度相位误差。考虑校准精度及交通应用场景,提出了基于功率最小熵(MPE)的误差自校准方法,随机生成误差向量作为优化初值,通过自适应优化算法搜索最小熵值对应的误差向量,实时校准各影响因素带来的误差。该方法无需离线可控环境中进行,并且无需预先估计目标数目及方位角。所提算法的推导、暗室实测和场景仿真数据的分析结果,证实了算法的有效性和优越性。

Error calibration method for millimeter wave traffic radar based on minimum entropy of power

Traffic radar uses MIMO technology to achieve the goal of obtaining high angular resolution with a small degree of freedom. However, due to factors such as highly integrated hardware processing technology and device aging, there are amplitude and phase errors between the channels of millimeter wave MIMO radar. Considering the calibration accuracy and traffic application scenarios, this paper proposes an error self-calibration method based on the minimum entropy of power(MPE). The error vector is randomly generated as the initial value of optimization, and the error vector corresponding to the minimum entropy is searched through an adaptive optimization algorithm, and each is calibrated in real time. Errors caused by influencing factors. The paper gives the derivation of the algorithm, the analysis results of the darkroom measured data and the actual scene simulation data, which proves the effectiveness and superiority of the proposed algorithm.