Synergism of binocular and motion stereo for passive ranging

Range measurements to objects in the world relative to mobile platforms such as ground or air vehicles are critical for visually aided navigation and obstacle detection/avoidance. An approach is presented that consists of a synergistic combination of two types of passive ranging method: binocular stereo and motion stereo. We show a new way to model the errors in binocular and motion stereo in conjunction with an inertial navigation system (INS) and derive the appropriate Kalman filter to refine the estimates from these two stereo ranging techniques. We present results using laboratory images that show that refined estimates can be optimally combined to give range values which are more accurate than any one of the individual estimates from binocular and motion stereo. By incorporating a blending filter, the approach has the potential of providing accurate, dense range measurements for all the pixels in the field of view (FOV)     

Recursive 3-D motion estimation from a monocular image sequence

Consideration is given to the design and application of a recursive algorithm to a sequence of images of a moving object to estimate both its structure and kinematics. The object is assumed to be rigid, and its motion is assumed to be smooth in the sense that it can be modeled by retaining an arbitrary number of terms in the appropriate Taylor series expansions. Translational motion involves a standard rectilinear model, while rotational motion is described with quaternions. Neglected terms of the Taylor series are modeled as process noise. A state-space model is constructed, incorporating both kinematic and structural states, and recursive techniques are used to estimate the state vector as a function of time. A set of object match points is assumed to be available. The problem is formulated as a parameter estimation and tracking problem which can use an arbitrarily large number of images in a sequence. The recursive estimation is done using an iterated extended Kalman filter (IEKF), initialized with the output of a batch algorithm run on the first few frames. Approximate Cramer-Rao lower bounds on the error covariance of the batch estimate are used as the initial state estimate error covariance of the IEKF. The performance of the recursive estimator is illustrated using both real and synthetic image sequences     

On-Line Vehicle Motion Estimation from Visual Terrain Information Part I: Recursive Image Registration

This paper addresses estimation of motion from the optical flow observed by an airborne down looking electro-optical sensor. The paper is in two parts. Part I addresses the development and analysis of a velocity-to-height ratio estimation algorithm and its principal error characteristics. In part II, it is shown how the information provided by the motion estimator can be integrated with additional on-board sensors to provide a complete autonomous navigation system. Part I as presented here is a summary version of the full length paper.? The algorithm implements recursive registration of successive images by using the gradient of a similarity function between them to control the tracking of their relative shift. The shift estimate provides velocity/height information. Substantial saving in memory and computation as compared to conventional full frame registration is achieved by using only a single line in the TV frame. Stochastic mathematical models for the image, terrain and vehicle velocity perturbations are used in the analysis. The choice of the most appropriate similarity function in the registration algorithm is addressed. Performance analysis indicates very small error variances, as illustrated by numerical examples.     

Error analysis of combined optical-flow and stereo passive ranging

Optical-flow ranging in which the stream of two-dimensional images obtained from a forward-looking forward-moving passive sensor is used to compute range to points in the field of view, and triangulation based on stereo images obtained from at least two stationary sensors are combined. The potential accuracies of the combined optical flow and stereo passive-ranging system are analyzed in the context of helicopter nap-of-the-earth obstacle avoidance. The Cramer-Rao lower bound (CRLB) is developed for the combined system under the assumption of a random angular misalignment common to both cameras of a stereo pair. It is shown that the range accuracy degradations caused by misalignment are negligible compared to those for a monocular optical-flow system     

惯性/双目视觉里程计深组合导航方法

针对现有视觉里程计测量噪声大、匹配精度低、实时性差的问题,研究一种基于Kalman滤波器的惯性/双目视觉里程计组合导航方法.在视觉里程计中引入惯性导航信息,辅助完成实时图截取、搜索区预测、输出速度校正等功能,提高视觉里程计的测量精度与计算速度.利用Kalman滤波器,实现视觉里程计对惯导累计误差的修正,提升组合导航系统的导航精度.车载试验结果表明,惯性/双目视觉里程计深组合导航的实时定位精度优于0.5％D (CEP),具备工程应用条件.     

A system for obstacle detection during rotorcraft low altitudeflight

An airborne vehicle such as a rotorcraft must avoid obstacles like antennas, towers, poles, fences, tree branches, and wires strung across the flight path. Automatic detection of the obstacles and generation of appropriate guidance and control actions for the vehicle to avoid these obstacles would facilitate autonomous navigation. The requirements of an obstacle detection system for rotorcraft in low-altitude Nap-of-the-Earth (NOE) flight based on various rotorcraft motion constraints is analyzed here in detail. It is argued that an automated obstacle detection system for the rotorcraft scenario should include both passive and active sensors to be effective. Consequently, it introduces a maximally passive system which involves the use of passive sensors (TV, FLIR) as well as the selective use of an active (laser) sensor. The passive component is concerned with estimating range using optical flow-based motion analysis and binocular stereo. The optical flow-based motion analysis that is combined with on-board inertial navigation system (INS) to compute ranges to visible scene points is described. Experimental results obtained using land vehicle data illustrate the particular approach to motion analysis     

基于双目视觉和惯性器件的微小型无人机运动状态估计方法

针对微小型无人机(UAV)自主运动状态估计问题,提出了一种基于双目视觉和惯性器件的微小型无人机运动状态估计方法,运动状态估计系统由微惯性测量单元(MIMU)和2个摄像机组成.根据微惯性测量单元的输出更新无人机运动状态,同时由摄像机获得周围环境的图像序列,从序列图像中提取特征点,并对这些特征点进行匹配、跟踪,测量序列图像...     

Identification of the state-space model and payload mass parameter of a flexible space manipulator using a recursive subspace tracking method

The on-orbit parameter identification of a space structure can be used for the modification of a system dynamics model and controller coefficients. This study focuses on the estimation of a system state-space model for a two-link space manipulator in the procedure of capturing an unknown object, and a recursive tracking approach based on the recursive predictor-based subspace identification (RPBSID) algorithm is proposed to identify the manipulator payload mass parameter. Structural rigid motion and elastic vibration are separated, and the dynamics model of the space manipulator is linearized at an arbitrary working point (i.e., a certain manipulator configuration). The state-space model is determined by using the RPBSID algorithm and matrix transformation. In addition, utilizing the identified system state-space model, the manipulator payload mass parameter is estimated by extracting the corresponding block matrix. In numerical simulations, the presented parameter identification method is implemented and compared with the classical algebraic algorithm and the recursive least squares method for different payload masses and manipulator configurations. Numerical results illustrate that the system state-space model and payload mass parameter of the two-link flexible space manipulator are effectively identified by the recursive subspace tracking method.     

A simple fixed-lag algorithm for tracking frequency rate-of-change

A family of simple fixed-lag frequency smoothing algorithms which provide good estimates of both frequency and frequency rate-of-change is reported. The smoothers were developed from a fixed-gain αβ tracker by replacing the recursive derivative estimator with a finite-impulse-response (FIR) differentiator. Simulation results are presented which show that the smoothing algorithms provide frequency estimates with a similar variance to those produced by the αβ filter but with greatly improved frequency-rate estimates. The smoothing algorithms and the αβ filter are also compared on the basis of the bias and delay introduced in the frequency-rate estimates. Although the results presented are for frequency estimation, the smoothing algorithms can be used in any single-input tracking application where some lag in the estimates is allowable     

Enhanced target detection using stereoscopic imaging radar

An earlier correspondence reported experiments which suggested that the visibility of a target in clutter could be improved through stereoscopic viewing of high resolution radar images. Here we provide a more thorough discussion on the application of stereo for improving radar detection and recognition. Experiments are reported which confirm and extend the earlier reported results. An example of the use of stereo in a practical system is provided which demonstrates the potential for acquisition of high quality radar stereograms     

Estimation of singularities for intercept point forecasting

In this paper, a recursive approach (an algorithm for estimation of singularity (AES)) is proposed to forecast the intercept point of a target and the pursuing interceptor recognized as the estimated singularity of a nodal cubic curve fitted to the data. The data comprises direction of arrival (DOA) estimates of both target and interceptor obtained at regular intervals of time using the maximum likelihood (ML) DOA estimation method. The estimates of coefficients of the cubic polynomial are given by a recursive least squares solution. From these coefficients, closed-form solutions for angle of interception and intercept time are obtained which are the forecasted coordinates of the intercept point. Experimental results demonstrate performance of the proposed algorithm     

Estimating Range Derivatives Using Phase Differences

The problem of estimating radar range derivatives using phase differences is considered. A minimum-variance, unbiased estimator is obtained. The resultant variances of the estimates so obtained are shown to be significantly lower than those of a least-squares estimator. Finally, a recursive form for the estimator is derived.     

基于距离子带的机载SAR高精度多级空变运动补偿

运动补偿（MOCO）是机载合成孔径雷达（SAR）获取高质量图像的关键,超高分辨率成像中,如何精确、高效地校正空变运动误差仍是很大的挑战。本文提出了一种改进的多级空变运动补偿方案,兼顾处理的精度和效率。首先,采用一步运动补偿法有效去除运动误差的距离空变分量,避免引起额外的距离徙动校正（RCMC）误差。同时,修正视线方向误差的传统计算方式,保证相位精度的前提下结合距离子带实现无插值的近似距离包络补偿。然后,利用距离子带降低残余方位空变误差的距离空变性和对方位时频关系的影响,显著改善宽波束情况下的聚焦效果,降低孔径依赖补偿算法的运算量。最终分辨率达到0.1 m,具有实际工程应用价值。点目标仿真和实测数据处理验证了所做的研究。     

Microsatellite Laser Altimeter

A feasibility study is presented of a laser altimeter conceived as an auxiliary device of an imaging camera to perform stereo pairs correction by high accuracy range measurements. System configuration is compliant to microsatellite constraints and is integrated to a high-resolution imaging sensor. System performance analysis is carried out by means of analytical models and computer codes and plots are presented to select key parameters allowing definition of a preliminary laser altimeter configuration     

用于SAR运动补偿的DGPS/SINS组合系统研究

使用考虑位置误差相关项的伪距率观测模型 ,研究了用于合成孔径雷达运动补偿的差分 GPS/ SINS伪距率组合系统。结果表明 ,组合系统的长期位置精度能达到 1 m左右。 GPS数据更新率低于 INS,在 GPS测量时间间隔内 ,组合系统的性能仅由 INS决定。虽然 INS误差随时间积累 ,在 GPS数据更新率为 1 s的情况下 ,即使采用中等精度的惯性仪表 ,其相对位置精度为厘米级 (这里相对位置精度指组合系统在 GPS测量时间间隔内位置误差的变化范围)。     

基于数值计算的机载SAR空变运动补偿算法

针对机载合成孔径雷达(SAR)高分辨率宽测绘带(HRWS)成像问题,在分析结合两步运动误差补偿的距离徙动算法基础上,提出一种基于数值计算的空变运动误差补偿算法。通过对粗聚焦图像进行分块,在子块的两维波数域进行空变运动补偿,补偿的相位包括方位相位误差、距离相位误差以及方位和距离的耦合相位,因此该算法在复杂航迹、高分辨和宽测绘带情况下仍具有较好的鲁棒性。最后对SAR仿真数据和实测数据进行处理,并与结合两步运动误差补偿的距离徙动算法进行比较,处理结果表明该算法能够更好地补偿空变运动误差。     

Estimation of Aircraft Target Motion Using Orientation Measurements

A new approach to estimating motion of a highly maneuverable aircraft target in an air-to-air tracking scenario is presented. An interactive filter system is developed that provides an improved estimate of target motion states by conditioning kinematic filter estimates on target aspect angle data. Pattern recognition techniques used with an electrooptical tracker are presumed to provide this target aspect information. A target orientation filter processes the aspect angle measurements by statistically weighting measured aspect angles with the current best estimate of target kinematics. The aerodynamic lift equation is used to relate approximate angle of attack to target velocity and acceleration. A novel statistical model for aircraft target normal acceleration is also developed to represent better the unknown target accelerations. Simulation results of realistic three-dimensional scenarios are presented to evaluate the performance of the interactive filter system.     

基于平面模板自由拍摄的双目立体测量系统的现场标定

 摄像机标定是基于光学摄像的立体测量技术中的一个十分重要的步骤，标定精度直接影响系统测量的精度和稳定性。本文提出并实现了一种简便易行的双目立体测量系统现场标定方法：利用一块特殊设计的具有不同大小圆形特征点的平面标定板，在无需控制任何运动参数的情况下，双目测量系统只需对标定板在不同角度自由拍摄一组图像即可方便地实现系统标定。该方法在已有单摄像机标定算法的基础上，加入对双摄像机相对位置和姿态的优化，同时考虑了镜头的非线性畸变，达到了较好的标定结果。另外，提出的图像点与其空间点的对应算法具有良好的稳定性，即使由于环境或摄像机摆放位置等因素的影响，一些标定板上的特征点不能被摄像机拍摄到，或者不能被正确识别时，仍然能进行标定工作。标定实验和系统标定后的三维重建结果验证了该方法的有效性。     

Accurate solution of proportional navigation for maneuveringtargets

An accurate solution is presented of the nonlinear differential equations describing motion under proportional navigation when the target is laterally maneuvering. A quasilinearization (QL) approach is used, followed by a perturbation technique to obtain closed-form solutions for trajectory parameters. An explicit expression for the pursuer lateral acceleration is derived and shown to contain contributions due to initial heading error and target maneuver, with a coupling between the two effects. The solution is shown to be a substantial and consistent generalization or an earlier accurate solution for nonmaneuvering targets and also of classical linear solutions for maneuvering targets. The generalized QL solution presented provides very accurate estimates of pursuer lateral acceleration over a much broader range of engagement geometries and target maneuvers than presently available closed-form solutions     

频域内参数估计

研究了在频域中利用方程误差法结合递推的傅里叶变换技术进行线性系统实时参数估计的方法。分别从频域中的方程误差法、递推的傅里叶变换和计算频率范围选择三个地参数估计进行了较详细地分析。通过结某型战斗机进行模拟计算，结果表明：该方法能自动过滤噪声；占用计算机内存固定；计算量小；不需要输入任何初值并在计算中调整任何参数；所估计的参数值能够在系统模态周期１．０￣１．５倍的时间内逼近真值，即使在信号水平较低的情