摘要
介绍了利用图像对比度最大法则估计多普勒调频率的原理方法,建立了多普勒调频率和图像对比度之间的数学模型。同时,介绍了启发式搜索算法原理,利用该算法估算每个调频率节点到目标调频率点的代价或估值,以估值最小的节点作为当前调频率节点,不断探寻新的子节点,并更新当前节点,最终收敛到目标点,即可以得到最优的调频率点。基于启发式搜索的对比度最优调频率估计算法的估计精度较高,运算效率较高。最后,利用实测数据处理结果验证该算法的有效性。
In this paper, theory of Contrast Optimization Autofocusing Algorithm （COAA） is introduced. Then the relation between Doppler chirp rate and imaging contrast is modeled, using the enlightened research algorithm. In this algorithm, the cost or esti- mated value of the Doppler chirp rate point to the target point is estimated. Then, the point which has the minimal cost is set to be the current Doppler chirp rate point and the current point will be updated after the searching of new child-points. Finally, these points will be made converged to the target points. This algorithm can estimate the Doppler chirp rate precisely. Imaging results for measured SAR data proved the validity of this algorithm.
出处
《现代雷达》
CSCD
北大核心
2009年第4期55-60,共6页
Modern Radar
基金
国家自然科学基金资助(60502044
60802081)
关键词
合成孔径雷达
多普勒调频率
对比度最大
启发式搜索算法
synthetic aperture radar
Doppler chirp rate
contrast optimization
enlightend search algorithm
