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341.
针对多目标跟踪粒子概率假设密度滤波算法中存活粒子的重要性密度采样问题,给出一种结合最新量测信息的存活粒子重要性密度采样新方法.该方法根据最新量测集中的各个最测与目标粒子的单步预测状态的似然值,以概率选取量测值,利用无迹变换获得粒子的重要性密度函数,并对其进行采样实现粒子概率假设密度滤波中存活粒子的采样,有效地减轻了粒子的退化现象. 3目标跟踪仿真试验中,当目标模型与跟踪算法使用的目标模型不匹配时,采用所提出的存活粒子采样方法的粒子概率假设密度滤波算法最优子模式分配距离下降约70km.论文给出的存活粒子采样新方法显著地提高了多目标跟踪粒子概率假设密度滤波算法的鲁棒性. 相似文献
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343.
针对无人地面车辆经典轨迹跟踪控制方法的不足,提出了一种基于无人地面车辆运动学模型的轨迹跟踪控制算法。在算法中引入了位姿的纵坐标误差,以加快跟踪的逼近速度,并利用人工驾驶的思想,采用了一种位一姿交替控制的方法,使路径跟踪既准确又快速。仿真结果表明:该方法是有效的,且可使无人地面车具有更好的跟踪性能。 相似文献
344.
为提高科氏流量计的计量精度,促进相关数字信号处理方法与技术的发展和进口高精度科氏流量计的国产化,设计了一种可移动式科氏流量计实验平台。简述了科氏流量计的基本原理和相关数字信号的处理方法,指明了相关方法的研究趋势。针对研究趋势,分析了科氏流量计实验平台的功能需求,给出了总体设计方案、硬件选型、软件流程和技术指标,重点阐述了数据采集模块(以PLC和NI9234为核心部件)的详细设计,给出了实验平台的初步测试结果。测试表明,该实验平台性能稳定,功能全面,能较好地为开展科氏流量计相关数字信号处理方法研究提供平台支撑。 相似文献
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针对常规舰炮武器系统对低照度、低反射面积目标无法自动跟踪和有效测距的情况,设计了一种基于光电传感器目标视频的手动跟踪及射击控制方法。操作手控制跟踪器对目标实时瞄准,并通过激光测距或距离装定,以获取目标的量测数据。该方法原理简单、成本低、易于实现,并且具有诸元快速校正功能,已成功应用于工程实践,并经过试验验证,可以有效提高系统对该类目标的作战能力。 相似文献
347.
The Signal‐to‐Interference‐plus‐Noise Ratio (SINR) is an important metric of wireless communication link quality. SINR estimates have several important applications. These include optimizing the transmit power level for a target quality of service, assisting with handoff decisions and dynamically adapting the data rate for wireless Internet applications. Accurate SINR estimation provides for both a more efficient system and a higher user‐perceived quality of service. In this paper, we develop new SINR estimators and compare their mean squared error (MSE) performance. We show that our new estimators dominate estimators that have previously appeared in the literature with respect to MSE. The sequence of transmitted bits in wireless communication systems consists of both pilot bits (which are known both to the transmitter and receiver) and user bits (which are known only by the transmitter). The SINR estimators we consider alternatively depend exclusively on pilot bits, exclusively on user bits, or simultaneously use both pilot and user bits. In addition, we consider estimators that utilize smoothing and feedback mechanisms. Smoothed estimators are motivated by the fact that the interference component of the SINR changes relatively slowly with time, typically with the addition or departure of a user to the system. Feedback estimators are motivated by the fact that receivers typically decode bits correctly with a very high probability, and therefore user bits can be thought of as quasipilot bits. For each estimator discussed, we derive an exact or approximate formula for its MSE. Satterthwaite approximations, noncentral F distributions (singly and doubly) and distribution theory of quadratic forms are the key statistical tools used in developing the MSE formulas. In the case of approximate MSE formulas, we validate their accuracy using simulation techniques. The approximate MSE formulas, of interest in their own right for comparing the quality of the estimators, are also used for optimally combining estimators. In particular, we derive optimal weights for linearly combining an estimator based on pilot bits with an estimator based on user bits. The optimal weights depend on the MSE of the two estimators being combined, and thus the accurate approximate MSE formulas can conveniently be used. The optimal weights also depend on the unknown SINR, and therefore need to be estimated in order to construct a useable combined estimator. The impact on the MSE of the combined estimator due to estimating the weights is examined. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004 相似文献
348.
以某运载火箭为例,介绍了将姿控系统数学模型转化为Simulink三通道仿真模型的方法和过程;在仿真过程中涉及到时变系数的瞬时时间固化法,分析由此引起的计算数据局部振荡,并提出解决办法;分析了用Simulink为该大型系统建模时所遇到的代数循环问题,并加以解决。 相似文献
349.
Tracking maneuvering target in real time autonomously and accurately in an uncertain environment is one of the challenging missions for unmanned aerial vehicles(UAVs).In this paper,aiming to address the control problem of maneuvering target tracking and obstacle avoidance,an online path planning approach for UAV is developed based on deep reinforcement learning.Through end-to-end learning powered by neural networks,the proposed approach can achieve the perception of the environment and continuous motion output control.This proposed approach includes:(1)A deep deterministic policy gradient(DDPG)-based control framework to provide learning and autonomous decision-making capa-bility for UAVs;(2)An improved method named MN-DDPG for introducing a type of mixed noises to assist UAV with exploring stochastic strategies for online optimal planning;and(3)An algorithm of task-decomposition and pre-training for efficient transfer learning to improve the generalization capability of UAV's control model built based on MN-DDPG.The experimental simulation results have verified that the proposed approach can achieve good self-adaptive adjustment of UAV's flight attitude in the tasks of maneuvering target tracking with a significant improvement in generalization capability and training efficiency of UAV tracking controller in uncertain environments. 相似文献
350.
粗瞄系统以直流力矩电机驱动二维转台为执行机构,通过粗瞄控制器对其进行控制。对系统受到的扰动进行分析,应用了最速跟踪微分器提取速度信号;以二维转台的方位轴为控制对象,在其位置环、速度环采用级联线性自抗扰控制器,通过线性扩张状态观测器主动补偿扰动,达到内外环双重隔离扰动的目的,提高跟踪精度;之后进行了实验分析。分析结果表明:在加入同样的模拟扰动信号,输入2 Hz,5 Hz和8 Hz的正弦信号时,与比例、微分、积分控制器相比,跟踪误差的标准差约降低50%;验证了线性扩张状态观测器具有扰动补偿效果;在输入不同频率正弦信号时,自抗扰控制器对输入信号频率的变化不敏感,仍能保证较高的跟踪精度。 相似文献