| 石桂欣,鄢社锋,刘宇.水下目标跟踪的改进非线性滤波快速算法*[J].,2020,39(1):91-96 |
| 水下目标跟踪的改进非线性滤波快速算法* |
| Improved Simplified Unscented/ Cubature Kalman filter algorithm for underwater target tracking system |
| 投稿时间：2019-04-17 修订日期：2019-12-24 |
| 中文摘要: |
| 由于水下作业中更换设备电源十分困难,通常希望算法的功耗比较低,以延长设备的工作寿命。无迹卡尔曼滤波(Unscented Kalman Filter, UKF)和容积卡尔曼滤波(Cubature Kalman Filter, CKF)算法是水下目标跟踪中常用的滤波算法。为了更好应用这两种算法,结合水下目标跟踪场景的实际特点,推导了两种算法在线性状态方程条件下的简化形式,新算法可以降低25%~50%左右的运算复杂度。仿真实验和湖试实验结果表明,提出的简化方法显著降低了运算量,平均运行时间减少30%以上,而精度与原算法相同,可以更好地满足水下目标跟踪系统的低功耗需求。 |
| 英文摘要: |
| Since most underwater devices are powered by batteries, computation load of algorithms is expected to be as light as possible. The simplified forms of Unscented Kalman Filter (UKF) and Cubature Kalman Filter (CKF) are derived, under the condition that the target state model is linear. The new algorithms can reduce the computational complexity by about 25%~50%. The experimental results show that the proposed simplified algorithms can significantly reduce the computation load, while the accuracy maintains, therefore the low power requirements of the underwater target tracking system can be met. |
| DOI：10.11684/j.issn.1000-310X.2020.01.011 |
| 中文关键词: 水下目标跟踪,容积卡尔曼滤波,无迹卡尔曼滤波 |
| 英文关键词: Underwater target tracking, Cubature Kalman Filter, Unscented Kalman Filter |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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