基于改进对数极坐标变换的星图识别算法

Star Map Recognition Algorithm Based on Improved Log-Polar Transformation

星图识别的速度决定了姿态更新率。针对基于对数极坐标变换的星图识别算法的循环位移带来的耗时问题,提出了一种改进算法。首先寻找距离视场中心最近的星点来构造新的直角坐标系,并转换为极坐标,然后将星点坐标投影至距离轴,构造星模式的特征向量。由于极坐标变换在距离轴上具有旋转不变性,所以避免了循环位移带来的耗时问题。仿真表明,所提算法平均识别时间减少到传统算法的8.4%,受到位置噪声影响时的识别率下降趋势更小,受到伪星和缺星影响时的识别率依旧高于传统算法。由于受到噪声影响时星模式相较于由恒星构成的三角形模式改变较大,所提算法的识别成功率总体上仍会低于三角形识别算法。

The speed of star map recognition determines the attitude update rate.To solve the time-consuming problem of cyclic displacement in the star map recognition algorithm based on log-polar transformation,we improve the algorithm.First,we search for the star point nearest to the center of the field of view,and construct a new rectangular coordinate system.The rectangular coordinates are then converted to polar coordinates.After projecting the star coordinates onto the distance axis,we construct a feature vector of star patterns.Because the polar coordinate transformation is rotationally invariant on the distance axis,the time-consuming problem causing by the cyclic displacement is avoided.In a simulation evaluation,the average recognition time of the proposed algorithm was reduced to 8.4%that of the traditional method,but this performance was slightly degraded by positional noise.The recognition rate of the proposed algorithm was higher than that of the traditional algorithm when the data were affected by pseudostars and missing stars.Under the influence of noise,star patterns are more changeable than triangle patterns,so the ecognition rate of the proposed algorithm is generally lower than that of the triangle-recognition algorithm.