战车主动防护系统中的目标跟踪算法研究

【作者】 高学刚；

【导师】 钱龙军；

【作者基本信息】 南京理工大学 ， 导航、制导与控制， 2010， 硕士

【摘要】 在现代局部战争中,装甲战车仍承担着重要的角色。装甲车辆主动防护系统为提高其在战场上的生存能力提供了重要的保障,许多军事强国都对其展开积极的研究。目标跟踪技术的研究对主动防护系统的研制至关重要,因此,深入研究近程或超近程机动目标跟踪算法及其关键技术,具有重要的理论和应用价值。为了精确地跟踪来袭目标,本文着重研究带径向速度量测的近程目标跟踪问题,并提出相应的滤波算法。通过对典型目标跟踪算法进行系统的分析和研究,提出了一些改进或优化的方法,并进行了仿真验证。本文主要成果和创新点包括以下三个方面：首先,为解决主动防护系统要求目标跟踪精度高、反应速度快等问题,考虑引入径向速度量测且设计了带径向速度量测的EKF、UKF、DCMKF滤波器,并通过仿真表明正确应用径向速度量测可以显著的提高跟踪性能。其次,提出了一种推广至三维的改进的带径向速度的DCMKF算法即基于坐标变换的非传统扩展卡尔曼滤波(AEKF),对其进行理论上的推导、证明与仿真验证。接着,基于CV模型、Singer模型将其与其它带径向速度的滤波器针对近程目标进行跟踪性能和运算速度的比较,证实本算法的有效性、适用性,优于其它几种算法。最后,分析相关系数、采样频率、量测误差方差等对改进算法跟踪性能的影响且辅以仿真图例,并基于工程实例对本文提出的算法进行验证、分析,为工程实际应用提供一定的理论上和工程上的参考。更多还原

【Abstract】 The armored vehicles will play an indispensable role in the modern regional war. Many military powerful countries have started the works on active protection systems for armored vehicle so that the survivability of armored vehicles will be improved on the battlefield. Target tracking technology is essential to active protection system researches. Therefore, it is very useful in theory and application to study short-range or ultra-short-range target tracking algorithms and techniques thoroughly in developing the active protection systems of armored vehicles.In order to track the coming targets accurately, this paper focuses on short-range target tracking with the radial velocity measurements and corresponding filter algorithms. Through systematic analysis and research, some filter algorithms are improved and some typical target tracking algorithms are analyzed with numerical simulations. Main results and improvements are listed in the following.Firstly, radial velocity measurements are introduced for designing the EKF, UKF, DCMKF filter so that they meet the performance indices such as high precision and quick response for target tracking of active protection system. The simulation results show that the tracking performance can be improved significantly by using the designed algorithm properly.Secondly, improved EKF algorithm with radial velocity is proposed by extending the results in two-dimensional case to that of three-dimension, namely alternative extended Kalman filter(AEKF). Based on CV and the Singer model for short-range or ultra-short-range target, the difference between this algorithm and others results on tracking performance and calculation speed are analyzed. It is verified that this algorithm more feasible than other methods.Finally, based on engineering and application background, this paper analyses the effect of the parameter changes of the correlation coefficient, the sampling frequency and measurement error variance to the tracking performance of the improved algorithms with simulation methods. This algorithm is also verified and analyzed by examples from practical project, which may be useful to theory and engineering application.更多还原