联合ADS-B的最小二乘雷达系统误差估计方法

为了解决两坐标雷达系统误差估计问题，提出一种联合ADS-B的最小二乘雷达系统误差估计方法.提出方法首先将ADS-B量测从地理坐标系转换到雷达局部直角坐标系，建立统一的配准空间；其次以雷达航迹的采样时间为基准，对ADS-B航迹进行插值，构造新的ADS-B航迹；然后采用直线拟合算法分别计算雷达航迹和ADS-B航迹的直线方程，并计算两条直线的夹角，再利用该夹角补偿雷达航迹的航向角数据；最后采用最小二乘算法估计雷达系统误差.实测数据实验结果表明，与传统直线拟合方法和最小二乘方法相比，提出方法能够更有效地估计雷达系统误差；经过提出方法配准处理后，雷达航迹数据的平均斜距离误差和方位角误差分别降低71.7%和52.7%.

Least Squares Radar Systematic Error Estimation Algorithm By Joint ADS-B

To solve the systematic error estimation problem for a two-coordinate radar, the least squares radar systematic error estimation method by a joint ADS-B (Automatic Dependent Surveillance-Broadcast) device is proposed. In the proposed method, the ADS-B measurements are first transformed from geographic coordinate system to radar local rectangular coordinate system for building a unified observation space. Then, the radar track and ADS-B track are applied to calculate the corresponding straight-line equation by the line fitting algorithm, and these two equations are further utilized to calculate the angly between the two straight-lines for compenlating the azimuth component of the radar track. Finally, the least squares algorithm is applied to estimate the radar systematic error. The real-data experimental results of real data illustrate that the proposed method can effectively estimate the radar systematic error compared with the traditional straight-line algorithm and the least squares algorithm. After registering the radar track by the proposed method, the average range error and the azimuth error can be reduced by 71.7% and 52.7%, respectively.