【摘要】 基于动态规划的TBD算法是检测微弱目标的有效方法,但在多帧积累中的动态规划处理会导致目标和强噪声的扩散进而产生较多的虚警。提出了一种利用轨迹特征进行目标鉴别的新方法。该方法利用噪声引起虚警在轨迹上具有很强的随机性这一特点,基于多阶方向直方统计进行目标鉴别。另外,还提出了一种局部极大值法和方向直方统计法级联的目标鉴别方案。仿真结果表明,方向直方统计法在消除噪声引起的虚警和保留真实目标方面都有很好的效果。而新的级联鉴别方案对于噪声引起的虚警和目标扩散引起的虚警都有很好的鉴别效果。更多还原

【Abstract】 The TBD algorithm based on Dynamic Programming is an effective method for detecting dim target.But the DP process during the multi-frame integration causes the expansion of targets and strong noise which may produce a large amount of false targets.To reduce them,a new discrimination method which takes advantage of the feature of trajectory is proposed in this paper.The false alarm caused by noise reveals strong randomicity on its trajectory which is different from that caused by true target,and the new method based on the statistics of different level direction histogram can be used to reduce false targets caused by noise.Moreover a new concatenated discrimination scheme of SDH+LEV is proposed.The simulation indicates that the discrimination method of SDH is good for reducing false alarms caused by noise and preserving real targets at the same time.The concatenated discrimination scheme can delete false alarms caused by noise and targets expansion effectively.更多还原