雷达低空目标俯仰角跟踪的C2算法研究

在单脉冲测角体制下,由于多径回波信号的干扰,极大地降低了雷达低空目标仰俯角跟踪精度,甚至丢失目标。通过对多路径反射环境模型分析,得出了岸、海基单脉冲雷达低空目标跟踪时仰俯角测量误差的产生原因,提出将传统的多目标分辨算法(C2算法)应用于低角多径环境下目标俯仰角的跟踪测量,并在不同多径反射环境下对不同高度、不同飞行速度和飞行方向的目标进行了仿真,得到良好的仿真结果,表明该算法可较大地提高俯仰角跟踪测量精度。通过对仿真结果的分析,验证了该算法在低空目标跟踪中的有效性和可行性。     

超低空空投航迹倾角自适应跟踪控制

针对超低空空投下滑阶段考虑执行器输入死区、不确定性大气扰动以及模型存在未知非线性等因素干扰轨迹精确跟踪等问题,提出了一种自适应神经网络动态面跟踪控制方法.建立了含执行器输入死区的超低空空投载机纵向非线性模型,采用神经网络逼近模型中未知非线性函数,引入非线性鲁棒补偿项消除了执行器死区建模误差和外界扰动.应用Lyapunov稳定性理论证明了闭环系统所有信号均是有界收敛的.仿真验证表明,所提方法既保证了轨迹跟踪的精确性,又具有强鲁棒性.     

Switching control of morphing aircraft based on Q-learning

This paper investigates a switching control strategy for the altitude motion of a morphing aircraft with variable sweep wings based on Q-learning. The morphing process is regarded as a function of the system states and a related altitude motion model is established. Then, the designed controller is divided into the outer part and inner part, where the outer part is devised by a combination of the back-stepping method and command filter technique so that the ‘explosion of complexity’ problem is eliminated. Moreover, the integrator structure of the altitude motion model is exploited to simplify the back-stepping design, and disturbance observers inspired from the idea of extended state observer are devised to obtain estimations of the system disturbances. The control input switches from the outer part to the inner part when the altitude tracking error converges to a small value and linear approximation of the altitude motion model is applied. The inner part is generated by the Q-learning algorithm which learns the optimal command in the presence of unknown system matrices and disturbances. It is proved rigorously that all signals of the closed-loop system stay bounded by the developed control method and controller switching occurs only once. Finally, comparative simulations are conducted to validate improved control performance of the proposed scheme.     

Bernoulli particle flter with observer altitude for maritime radiation source tracking in the presence of measurement uncertainty

For maritime radiation source target tracking in particular electronic counter measures（ECM）environment,there exists two main problems which can deteriorate the tracking performance of traditional approaches.The frst problem is the poor observability of the radiation source.The second one is the measurement uncertainty which includes the uncertainty of the target appearing/disappearing and the detection uncertainty（false and missed detections）.A novel approach is proposed in this paper for tracking maritime radiation source in the presence of measurement uncertainty.To solve the poor observability of maritime radiation source target,using the radiation source motion restriction,the observer altitude information is incorporated into the bearings-only tracking（BOT）method to obtain the unique target localization.Then the two uncertainties in the ECM environment are modeled by the random fnite set（RFS）theory and the Bernoulli fltering method with the observer altitude is adopted to solve the tracking problem of maritime radiation source in such context.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source,and also demonstrate the superiority of the method compared with the traditional integrated probabilistic data association（IPDA）method.The tracking performance under different conditions,particularly those involving different duration of radiation source opening and switching-off,indicates that the method to solve our problem is robust and effective.     

基于超短基线声传感器阵的高速目标轨迹估计

针对低空高速飞行目标跟踪问题,首先研究了某典型目标噪声信号的时频特性,发现其信号呈现宽带低频特征,难以从频域对目标轨迹进行估计。在此基础上,从各路接收信号的到达时延量入手,考虑到声基阵只能布设于有限空间内的制约,提出了一种基于超短基线阵时延估计的目标跟踪方法。该方法利用各个超短基线阵接收声强极值点分别估计目标运动轨迹垂线方向,计算多个垂线的叉乘向量实现对目标运动方向的估计,再利用多面交汇的方式获估计得到目标运动轨迹。分别对目标俯仰角、方位角及运动轨迹估计的理论误差进行了推导,根据理论估计误差,为能够实现对目标运动轨迹的估计,各个超短基线阵应尽量保证与目标运动轨迹不在同一平面上。根据仿真结果,在采用4个传感器基阵时,角度估计平均误差在4°以内,位置估计相对误差在5%左右。仿真结果验证了该方法的有效性。     

固定翼无人机编队集结控制算法研究

针对固定翼无人机协同作战时的编队集结问题，提出了一种新的路径规划和位置分配方法，并设计了包括航迹跟踪、高度保持和速度控制在内的自动驾驶仪。该路径规划算法通过矩阵迭代得到一组较优的目标点分配方案，满足总航程较小和同时到达约束。根据得到的各无人机飞向目标点的航迹，算出无人机编队集结的代价矩阵。在每架无人机确定了应飞航路后，开始沿航路飞向目标点，在此过程中，纵向采用高度保持自动驾驶仪，横向采用航迹跟踪自动驾驶仪，控制无人机按规定航迹飞行。速度调节自动驾驶仪可根据速度指令调节油门大小加减速，跟踪上目标速度，进而实现编队集结。仿真结果验证了所提出的编队集结控制方法的有效性和可行性。     

A tracking approach for targets with measurements containingjamming or clutter signals

The concept of maneuvering target tracking which is presented by K. Demirbas, (see ibid., vol.AES-23, p.757-66, 1987) is used to track maneuvering targets whose observations contain interference representing jamming or clutter signals. The resulting tracking approach produces state estimates that closely follow the actual state values, as in target tracking in a clear environment     

近程反导舰炮拦截掠海目标供靶需求分析

针对舰炮武器系统设计定性试验供靶飞行速度低、飞行高度降不下来,且小航路捷径供靶实现难度大风险高,因此考核标准低,难以对舰炮武器系统进行有效充分考核等问题,从舰炮武器系统试验靶标供靶的速度、高度、航路捷径等方面分析了影响目标毁伤概率的因素,建立了毁伤概率计算模型。通过实际验算论证了近程反导舰炮拦截掠海导弹类目标时,如果目标速度低、飞行高度高、航路捷径大,对此类目标的毁伤概率将明显增大,导致武器系统考核标准降低。提出了为真实考核武器装备的作战效能,要采用速度高、掠海飞行、航路捷径小的靶弹类目标进行拦截试验,以解决试验的充分性、边界条件问题,实现从严考核之目的。     

Precise Decoupling Tracking of Airspeed and Altitude for UAV Based on Causal Solution of Stable Inversion

Use stable inversion to accomplish precise decoupling tracking of airspeed and altitude for conventional takeoff and landing of unmanned aerial vehicles (UAVs) is in essence a non-minimum phase output tracking problem. The main contribution of this article is that a new method to calculate the causal solution of stable inversion is proposed by introducing a well defined perturbed signal to the system's unstable internal dynamics. It is helpful to overcome the pitfalls resulting from non-causality in existing methods. Different from the mathematically accurate offline non-causal solution, the causal solution is an approximation with asymptotically convergent errors. The important merits are: It obviates the needs for the output trajectory to be pre-known time parameterized functions, hence broadening the application of stable inversion; The low computational workload is much more suitable for and beneficial to real-time applications than any existing method based on stable inversion. The output tracking problem is then converted into a state tracking problem based on the causal solution of stable inversion. Precise decoupling tracking of airspeed and altitude is realized by using a feedback controller. Simulations are carried out to verify the viability and low computational workload of the method.     

Disturbance observer-based backstepping control for hypersonic flight vehicles without use of measured flight path angle

In this paper a nonlinear control method is proposed for the tracking control of hypersonic flight vehicles. The designed control laws do not utilize the measured flight path angle due to its inferior accuracy in practical engineering. For this, an estimated flight path angle is designed via the measurements of the altitude and velocity. A tracking differentiator is designed for constructing nonlinear disturbance observer which is used to estimate the model uncertainties including the parameter indeterminacies and external disturbances in the channels of velocity and pitch rate. A robust high-order differentiator is introduced to avoid the employment of the measured flight path angle and estimate the lumped disturbance in dynamics of flight path angle. Meanwhile, the possible saturation of the control inputs is considered and compensated by the auxiliary states. The boundness of closed-loop signals is proved through the Lyapunov theory. Comparative simulations are carried out and the results demonstrate the effectiveness of the proposed method.     

Robust control for an unmanned helicopter with constrained flapping dynamics

In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints. For handling the state constraints, the barrier Lyapunov function and the saturation function are employed. And, the prescribed performance method is used to deal with the flapping angle constraints for the unmanned helicopter. It is proved that the proposed control approach can ensure that all the signals of the resulting closed-loop system are bounded, and the tracking errors are within the prescribed performance bounds for all time. The numerical simulation is given to illustrate the performance of the proposed scheme.     

Multipath Angle Error Reduction Using Multiple-Target Methods

The usual methods of reducing multipath angle errors in monopulse tracking radar achieve only limited success because they do not attack the root of the problem. A more correct approach is to accept the multipath signal as a second target and utilize a two-target signal processor which angle tracks both wavefronts. The processor will decouple the return signals so that relatively interference-free data on both waves are obtained. In this paper a signal processor for separating signal from (N - 1) multipath components is developed. The processor is then specialized to the case of only one multipath signal and evaluated by a computer simulation. Data show that large improvements are possible as compared to the usual monopulse tracking system. In particular, the usual large bias errors at low elevation angles are eliminated. Tracking precision compares favorably with the theoretically best possible for two-target tracking systems.     

Application of Recursive Estimation and Kalman Filtering to Doppler Tracking

The techniques of recursive estimation and Kalman filtering are applied to the problem of estimation of space vehicle orbits and trajectories using only measurements of the Doppler shifts in radio signals transmitted by or reflected from the target. Two approaches are described. One is a global fit technique in which the parameters of an assumed trajectory model are estimated. The second is a pointwise mapping technique in which the trajectory estimate is extrapolated as the target tracking data is received. The paper provides a tutorial illustration of the direct application of recursive optimization techniques to a class of engineering problems.     

扩频信号角跟踪带宽分析与优化

扩频信号由于带宽宽、信噪比低,难以实现对信号的角跟踪。本文在和差信号相关法提取角误差电压的基础上,利用小部分带宽法的一些原理,提出了和差信号小部分带宽相关的方法,提高了输出信噪比。     

基于人工神经网络的多模型目标跟踪算法

针对在目标跟踪中单模型跟踪算法难以应对目标运动形式的变化,而多模型跟踪算法存在结构固定、跟踪精度被非匹配模型削弱且模型切换缓慢的矛盾,文章提出了一种基于人工神经网络的多模型目标跟踪算法。通过分析目标几种基本运动模式的轨迹特点,归纳出目标运动轨迹的特征向量。利用训练好的BP神经网络对滑窗里的轨迹段进行运动模型识别,按结果进行跟踪模型切换,达到使跟踪算法实时适应目标运动状态的目的。仿真结果证明了该算法的有效性,且与传统的多模型算法相比,具有结构更加简单、更强的灵活性和拓展性的特点。     

一种高动态低信噪比下载波快速捕获跟踪方法

针对高动态、低信噪比的接收信号,首先对整个多普勒频率范围进行分段,并在每一段内利用本地产生的带有多普勒频率变化率的复信号来抵消接收信号中多普勒频率变化率的影响,然后在每一段内利用FFT（FastFourierTransform,快速傅里叶变换）进行载波频率并行捕获,从而同时完成载波多普勒频率及其变化率的初步估计。利用载波多普勒频率及其变化率估计信息辅助锁频环快速入锁,进而利用锁频环辅助三阶锁相环完成载波信号的锁频锁相跟踪。使用这种方法,可以快速获取信号的多普勒频率及其变化率信息,并且在极短时间内完成载波的稳定跟踪,使接收设备具备快速捕获跟踪大动态弱信号的能力。     

The Goddard Range and Range Rate Tracking System: Concept,design and performance

This paper is concerned with the concept, evolution and performance analysis of a high-accuracy, near-earth and cislunar cooperative target tracking system, known as the Goddard Range and Range Rate System.This system combines the advantages of harmonic (or sidetone) and pseudo-random coded ranging signals in a highly effective and versatile manner, operable either as an all-harmonic system in near-earth orbital tracking or as a hybrid system for tracking more distant spacecraft. The system also combines the utilization of the two types of signals in a very attractive technique for speeding up the process of acquiring the ambiguity resolving code component in tracking spacecraft at cislunar and translunar distances.The theoretical analysis of system performance and errors is followed by a summary of performance data gathered to date by operating GRARR systems on a number of NASA missions.     

极弱信号环境下GPS位同步和载波跟踪技术

为解决环路未锁定、无法找出正确的导航数据位跳变点时极弱全球定位系统(GPS)信号跟踪问题,通过分析信号跟踪模型和相关器1 ms采样数据特性,将最优路径动态规划算法应用于GPS位同步,并提出基于平方根无迹卡尔曼滤波(SRUKF)和位同步结合的载波联合跟踪算法。建立了适合位同步的SRUKF载波环参数估计模型,针对位同步的实现条件和无相位频率先验信息的情况,将位同步模块提前,研究设计了环路未锁定时串行和并行两种弱信号跟踪方案。位同步跟踪完成后环路采用单独的SRUKF工作方式。实验结果证实该文提出的算法具有较高的数据位边缘检测概率(EDR)和参数估计性能,而无须关心环路是否处于锁定状态,能够对载噪比低至22 dB/Hz的弱信号实现跟踪。     

基于RBFN的伺服系统前馈控制器设计和仿真研究

 以转台伺服系统为控制对象, 采用RBF 神经网络前馈控制和比例反馈相结合的方法, 并利用单神经元对系统模型进行在线辨识, 为前馈控制器提供Jacobian 参数。将该方法运用在速度环控制中, 仿真结果表明, 采用了该方法的控制系统, 具有较高的跟踪精度和动态性能。     

Altitude Estimation Using Asynchronous ? - ? Tracking Filters

In the analysis of the ?-? tracking filter it is usually assumed that the tracking filter and data source operate in synchronism at a constant data rate. However, in a multisensor environment in which the tracking algorithm operates at fixed intervals, the tracking filter cannot be synchronized with the sensors. An analytical solution is obtained for the case in which the tracking filter and data source operate asynchronously with a ?time-correction? process used to approximate the synchronous operation of the tracking filter. An example is given in which the effects of data quantization on the performance of an altitude tracking filter for air traffic control are examined. It is shown that the asynchronous operation of the tracking filter in the example without the time-correction process will result in significant errors in the predicted altitude.