基于不敏变换的动基座传感器偏差估计方法

提出了一种新的基于合作目标的动基座传感器误差绝对配准方法。该方法利用所获得的合作目标位置信息,将载体平台姿态角偏差转换为传感器测量偏差中的一部分,并建立偏差状态方程和测量方程。在此基础上,采用广义最小二乘方法以实现传感器测距误差的估计,不敏滤波的方法则用于实现平台载体的姿态偏差和角度测量偏差的实时估计。仿真结果表明,该方法实现简单,收敛速度快,可以实现单部动基座传感器的偏差估计。     

A simple smoother: closed-form solution and analytical results

A closed-form solid-state solution for a simple one-dimensional smoother is presented. The target position-velocity dynamics are modeled as a linear discrete Gauss-Markov process: the discrete position measurements are assumed to be independent and identically normally distributed. Analytical results derived from estimating optimum steady-state position and velocity are given as well as the improvement provided by smoothing relative to pure filtering estimates. Analytical results, including appropriate limiting cases, show that the ratios of the RMS smoothing to the RMS filtering error are from 1/2 to 1 in position and from 1/2 to 1/√2 in velocity. As a numerical example a highly maneuvering target characterized by an acceleration width of 30 m/s² is considered     

Navigation Accuracy Category-Position Models and Estimate Position Uncertainty Calculations for TIS-B System

Navigation accuracy category-position (NACp) is an important parameter for system accuracy of traffic information service-broadcast (TIS-B), which is determined by estimate position uncertainty (EPU). Centered about the problems that the existing EPU calculation based on noise measurement is low in accuracy and unfit for describing uncorrected biases in target reports, this article analyses the traditional NACp model, and uses the least square estimation (LSE) in EPU calculation. Furthermore, it proposes an extended NACp model, which considers both noise and biases and acquires EPU estimation with the help of approximate multiplex Taylor expression. Analysis and simulation show that the proposed method not only leads to significant improvement of the accuracy of EPU calculation, but is fit for EPU calculation with tracking biases in TIS-B system as well. As such it can find application in practice to depict different kinds of error models in TIS-B system.     

一种用于舰船CNS/RLG-SINS组合导航系统校准的分段估计方法研究

分析了“天文测姿+惯性导航”组合导航滤波模型的可观测性问题,在状态不完全可观的条件下,提出采用分段滤波的方法可以分别对加速度计误差和陀螺漂移误差进行有效估计,此方法仅要求每段滤波开始前外部提供一次准确的初始位置和速度信息。结合舰载导航需求背景,设计仿真模型。仿真结果表明：采用分段滤波方法,加速度计常值偏置和陀螺常值漂移均可以得到充分估计;对惯性器件误差进行标校、补偿后,24小时的位置误差可由补偿前的3.6海里减小到补偿后的0.5海里。     

基于视觉的惯性导航误差在线修正

陀螺零偏和加速度计零偏是影响惯性测量单元(IMU)积分精度的重要因素。提供一组精确的实时的零偏估计可以提高IMU的积分精度,为视觉导航提供良好的位姿预测,提高整个系统的动态性能。通过合理地建立IMU的噪声模型以及IMU和视觉的组合方程,利用一种基于李群和李代数知识的IMU预积分方法将零偏进行合理的线性化,运用Kalman滤波进行IMU零偏的在线估计。实验结果表明,通过本文的修正方法,惯性导航的平均积累误差由0.034m/s提高到0.0037m/s,精度明显提高。     

Infrared Systems: I. Accuracy of Angle Measurement

In this paper expressions are derived for the error in position measurement for the problem of estimating the position of an infrared target in a random background and the combined prob lem when white detector noise is also affecting the estimation. Space filters performing linear scanning, nutation, and rotation are considered. A linear scanning infrared system is then considered in greater detail. The noise on the error signal is calculated, taking into account both the estimation error, as discussed in the first part, and "false alarms" occurring in the scan area far from the target.     

ADS-B用于高精度雷达标定的方法

为了更好地解决高精度雷达标定的问题,提出了基于广播式自动相关监视系统(ADS-B)固定误差及目标回波中心动态修正的雷达标定新方法。首先分析了ADS-B位置数据误差的来源、类型及在雷达坐标系下的特征,同时对民航目标回波中心的变化作了分析建模,在此基础上进一步通过对雷达数据与ADS-B数据之差作动态联合修正,最终估算出雷达系统误差,提高了雷达系统误差标定的精度和稳定性。并利用多批次的实测数据对该标定新方法与其他方法进行了对比验证,结果表明,该方法有效提高了标定的精度和稳定性,并已成功应用于雷达标定设备中。     

基于脱靶量数据的发射系航迹参数求解方法

针对当前海态巡航飞行试验末段外测无法跟踪测量的实际问题,基于现有脱靶量测量系统,建立了利用某脱靶量测量数据到发射系的转换模型。此模型将脱靶量测量数据统一到发射系航迹中,有利于航迹分析工作。并建立了转换结果的误差估计模型,误差模型充分考虑了脱靶量测量误差、靶船定位误差以及靶船航向角误差。利用仿真数据对转换模型及误差模型进行了计算验证。结果表明,位置误差满足精度要求。该方法对延拓外测处理时段具有积极意义。     

Autonomous orbit determination using epoch-differenced gravity gradients and starlight refraction

Autonomous orbit determination via integration of epoch-differenced gravity gradients and starlight refraction is proposed in this paper for low-Earth-orbiting satellites operating in GPS-denied environments.Starlight refraction compensates for the significant along-track position error that occurs from only using gravity gradients and benefits from integration in terms of improved accuracy in radial and cross-track position estimates.The between-epoch differencing of gravity gradients is employed to eliminate slowly varying measurement biases and noise near the orbit revolution frequency.The refraction angle measurements are directly used and its Jacobian matrix derived from an implicit observation equation.An information fusion filter based on a sequential extended Kalman filter is developed for the orbit determination.Truth-model simulations are used to test the performance of the algorithm,and the effects of differencing intervals and orbital heights are analyzed.A semi-simulation study using actual gravity gradient data from the Gravity field and steady-state Ocean Circulation Explorer (GOCE) combined with simulated starlight refraction measurements is further conducted,and a three-dimensional position accuracy of better than 100 m is achieved.     

射频仿真幅相控制误差对目标位置精度的影响分析

在射频仿真系统中，精确的目标位置通过“三元组”幅相控制实现，幅相控制误差直接影响阵列上目标位置的模拟精度。详细推导了角闪烁方程，以此建立了幅控误差传播模型，提出了相控误差传播的等效分析方法，分析了幅相控误差对目标位置精度影响的基本规律。基本分析结论经仿真验证正确，具有工程指导意义。     

Statistical Analysis of Antenna Pattern Loss Effects

The generation of average probability-of-detection curves for threedimensional, or pencil-beam, radars, with compensation for random target position included statistically, is discussed. A fixed-array radar with step-scan operation is assumed and, with 3-dB beam crossover points, this is effectively the case of one pulse per beamwidth or one hit per scan. Numerical results are presented showing detection dependence on beam overlap, detection threshold, and amplitude scintillation. The fact that the average energy received from a target, assuming a uniform distribution of target position within a beam, does not lead to the correct average probability of detection at other than 0.5 P D is discussed and shown graphically.     

Discrete-time min-max tracking

The problem of optimal state estimation of linear discrete-time systems with measured outputs that are corrupted by additive white noise is addressed. Such estimation is often encountered in problems of target tracking where the target dynamics is driven by finite energy signals, whereas the measurement noise is approximated by white noise. The relevant cost function for such tracking problems is the expected value of the standard H/sub /spl infin// performance index, with respect to the measurement noise statistics. The estimator, serving as a tracking filter, tries to minimize the mean-square estimation error, and the exogenous disturbance, which may represent the target maneuvers, tries to maximize this error while being penalized for its energy. The solution, which is obtained by completing the cost function to squares, is shown to satisfy also the matrix version of the maximum principle. The solution is derived in terms of two coupled Riccati difference equations from which the filter gains are derived. In the case where an infinite penalty is imposed on the energy of the exogenous disturbance, the celebrated discrete-time Kalman filter is recovered. A local iterations scheme which is based on linear matrix inequalities is proposed to solve these equations. An illustrative example is given where the velocity of a maneuvering target has to be estimated utilizing noisy measurements of the target position.     

基于CADET的弹道交会误差变化规律分析

运载器弹道与预测命中点之间的交会误差是拦截器分离点误差引起的。分离点的位置误差、速度误差对于弹道交会误差的影响,既取决于其本身的大小,也取决于分离点到达预测命中点的时间。依据分离点误差推算弹道飞行的误差变化规律,是进行运载器制导控制系统分析与误差分配的前提条件。本文通过采用协方差分析描述函数法,对弹道误差变化规律进行了有效分析。仿真结果证明了这种方法的有效性。     

双轮移动机器人运动目标追踪与避障控制算法

 设计了双回路的双轮移动机器人运动目标追踪与避障控制方案。内层控制回路是运动目标追踪控制律，指导机器人追踪到目标并保持一定的安全距离，控制律考虑了机器人在运动速度上的限制，其渐近稳定性用Lyapunov函数法进行了证明。当遇到障碍物时，外层控制回路根据超声传感器的信息和阻抗控制的概念产生阻抗虚拟力，将期望目标调整到虚拟位置，使机器人能够自动转向以避开障碍物。仿真研究和实验结果证明了追踪算法的有效性和避障方法的可行性。     

Multisensor multitarget bias estimation for general asynchronous sensors

A novel solution is provided for the bias estimation problem in multiple asynchronous sensors using common targets of opportunity. The decoupling between the target state estimation and the sensor bias estimation is achieved without ignoring or approximating the crosscovariance between the state estimate and the bias estimate. The target data reported by the sensors are usually not time-coincident or synchronous due to the different data rates. Since the bias estimation requires time-coincident target data from different sensors, a novel scheme is used to transform the measurements from the different times of the sensors into pseudomeasurements of the sensor biases with additive noises that are zero-mean, white, and with easily calculated covariances. These results allow bias estimation as well as the evaluation of the Cramer-Rao lower bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases in any scenario. Monte Carlo simulation results show that the new method is statistically efficient, i.e., it meets the CRLB. The use of this technique for scale and sensor location biases in addition to the usual additive biases is also presented.     

Theoretical analysis of the sequential lobing technique

A theoretical analysis of the sequential lobing technique for target angle tracking is presented. The signal power received by each antenna beam is assumed to pass through a logarithmic amplifier. A rigorous statistical approach is adopted in the analysis for both non-fluctuating and fluctuating targets. Closed form expressions are derived for the normalized mean error and rms error of the angle estimate for Swerling 0, I, II, and III targets. Results are compared with those obtained using a simplified approach for the non-fluctuating target     

Error Analysis for Relay Type Satellite-Aided Search and Rescue Systems

An analysis is made of the errors in the determination of the position of an emergency transmitter in a satellite-aided search and rescue system. The satellite is assumed to be at a height of 820 km in a near-circular near polar orbit. Short data spans of four minutes or less are used. The error sources considered are measurement noise, transmitter frequency drift, ionospheric effects, and error in the assumed height of the transmitter. The errors are calculated for several different transmitter positions, data rates, and data spans. The only transmitter frequency used was 406 MHz, but the result can be scaled to different frequencies.     

改进的Chan-粒子滤波算法超宽带室内三维定位

针对超宽带室内定位时容易受到非视距误差的影响，导致定位精度大大下降，甚至无法准确定位的问题，提出了一种融合粒子滤波的改进Chan定位新方法。首先，在Chan定位方法中引入模拟退火算法，对到达时间差（TDOA）算法的测量值进行优化，获得初步定位的最优解；然后，采用粒子滤波对测量值进行再次优化，粒子重采样后得到的中心位置即为目标节点的精确位置。仿真和实验结果均表明，该算法能有效提高在非视距环境下超宽带室内定位的精度，较好地消除非视距误差的干扰。     

Optimum Steady-State Position and Velocity Estimation Using Noisy Sampled Position Data

The Kalman filtering technique is used to obtain analytical expressions for the optimum position and velocity accuracy that can be achieved in a navigation system that measures position at uniform sampling intervals of T seconds through random noise with an rms value of ?x. A one-dimensional dynamic model, with piecewise-constant acceleration assumed, is used in the analysis, in which analytic expressions for position and velocity accuracy (mean square), before and after observations, are obtained. The errors are maximum immediately before position measurements are made. The maximum position error, however, can be bounded by the inherent sensor error by use of a sufficiently high sampling rate, which depends on the sensor accuracy and acceleration level. The steady-state Kalman filter for realizing the optimum estimates consists of a double integrator, the initial conditions of which are reset at each observation.     

Multiple target tracking using products of position measurements

The continued development of the symmetric measurement equation (SME) filter for track maintenance in multiple target tracking (MTT) is considered, focusing on the case in which the SMEs are generated by forming sums of products of the original position measurements. The SME filter is developed for the case of N targets whose motions consist of random perturbations about constant-velocity trajectories. It is assumed that measurements of x-coordinate positions are available, and that the number of measurements is equal to the number of targets. Various analytical properties of the SME filter are studied. It is shown that under a very weak condition, the estimation error equation is locally exponentially stable. The performance of the SME filter is investigated by comparing it with an optimal (minimum-variance) estimator and by generating a computer simulation in the six-target case