Computation of aircraft geometric height under radar surveillance

A radar system for geometric height estimation of civil aircraft is described. The system consists of one standard or mode S secondary surveillance radar (SSR) and one omnidirectional antenna sited away from SSR under an airplane. The geometric height is derived by trilateration. Systematic errors are compensated for by deriving the profile of the effect on height measurements of the bias in range measurements. A curve-fitting technique is then used, which estimates both the geometric height and any non-zero systematic errors     

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。     

Doppler Radar Error Equations for Damped Inertial Navigation System Analysis

The use of Doppler radar measurements to provide velocity damping for an aircraft inertial navigation system is considered. Three different Doppler antenna configurations are examined: two-axis stabilized, azimuth stabilized, and data stabilized antennas. A general reference velocity error equation is presented and appropriately evaluated for each of the Doppler configurations. Specific elements of the error equations are examined and physically interpreted for both local-level and space-stable inertial systems. Detailed examination of the interaction of Doppler radar and inertial navigation velocity error mechanisms is provided.     

均方意义下三维雷达无偏转换测量误差协方差阵的推导

在以前的研究中,无偏转测量误差协方差阵是基于当前测量值得到的.为了能利用所有历史数据以得到更精确的转换测量误差协方差阵估计,文中在均方意义下,推导了三维雷达的最优无偏转换测量误差协方差阵.     

一种智能的惯导陀螺漂移误差消除算法

给出了一套智能的消除惯导陀螺漂移误差算法,即改进的BP(Back Propagation)神经网络模态识别算法。可根据即时的飞行区域、气压计和雷达高度表测量的地形高程数据等,在机载数字地图上实时地进行在线模态识别,找出最合适的匹配区,并对惯性导航系统指示的位置信息进行修正。该算法具有识别精度高、识别速度快和识别准确率高等特点,可用于各类有人驾驶飞行器和无人自主控制的飞行器的惯导误差修正。     

基于机载单天线雷达一维距离数据的地表三维信息优化重建方法

陆地的刚体表面在机载雷达的任意相对运动下具有几何不变性,基于此约束可利用雷达距离像中提取出的地面多个强散射点的一维距离数据,重建出地表的三维信息以及载机未知的运动轨迹.鉴于现有基于雷达远场假设的重建方法无法适用于具有较大近场误差的地面目标重建的问题,提出一种基于雷达近场几何模型的优化重建方法,采用非线性优化方法实现了对...     

Radar measurement accuracy for fluctuating targets

The impact of target radar cross-section (RCS) fluctuations on the thermal noise limited accuracy of radar measurements of range, range rate, and angle are evaluated for the Swerling fluctuation models. For large signal-to-noise ratios (SNRs), the accuracy criterion used is the measurement error with the same probability span as the one corresponding to the standard deviation points of the measurement error for the nonfluctuating model.<>     

复杂航迹和起伏地形条件下机载聚束SAR 空变运动补偿

 运动补偿是雷达平台机动飞行条件下合成孔径雷达(SAR)实现精确聚焦成像的前提,而如何精确实现运动误差的空变补偿(误差补偿随目标距离、方位和高度位置的变化而变化)目前还存在很大的挑战。本文提出了一种新的三阶运动补偿方法,能够有效解决复杂雷达航迹和地形起伏条件下运动误差的空变补偿问题。该方法首先以场景中心为参考进行空不变运动补偿,然后以多个子场景中心为参考进行空变运动补偿,最后再利用极坐标格式算法(PFA)统一补偿每个像素的空变误差。仿真数据处理结果验证了本文方法的有效性。     

Impact of target RCS fluctuations on radar measurement accuracy

The impact of target radar cross section (RCS) fluctuations on the thermal noise limited accuracy of radar measurements of range, range rate, and angle is evaluated for Swerling fluctuation models. The impact is expressed as a modification of the large-signal approximation to the standard deviation σ of measurement error     

Performance analysis of a radar target discrimination technique

The performance of a radar target discrimination technique using multiple-frequency scattering amplitude without phase data is investigated. Based on the concept of natural resonance frequencies, the technique is aspect independent so that a priori information of the aspect angle is not necessary. The radar cross sections (RCSs) of spheroids are calculated numerically to simulate the received radar returns for distinguishing different spheroids and wires in the resonance frequency range by the proposed technique. By Monte Carlo simulation, the discrimination error rate is estimated as a function of the standard deviation of added noise. The numerical results show that the discrimination algorithm works well under moderately noisy situations and can be applied even in a high-resonance frequency range     

Correspondence

Extraction of elevation information with phased array search radar in the presence of specular reflection from sea surface is presented. Specular reflection from sea causes large peak errors in the measurement of low elevation angle. An algorithm based on complex indicated angle is derived to reduce specular reflection component. From the complex indicated angle and the exactly known or approximately known data, the authors can generate a specular reflection error finding function (SREFF). SREFF clearly indicates where the measurements are much affected by the specular reflection in the complex indicated angle data     

一种基于单部雷达的飞行器脱靶量测试方法

对单部雷达测量飞行器脱靶量所涉及到的雷达分辨力和多目标信息获取及处理进行了分析;结合实际靶场应用介绍了脱靶量数据处理方法;分析了脱靶量的测量误差,并给出了分析结果;本方法可最大限度地补偿掉系统误差,脱靶量测量误差主要来源于雷达本身测量精度。     

Target Track Pulse Scheduling

The problem of scheduling radar tracking pulses in a dense target environment where the position estimation error must be constrained to avoid false return with track correlations is considered. The problem is to schedule n fixed energy pulses such that the rangerate error is minimized at some final time subject to the constraint that the position error will be smaller than some value for the whole time interval. For a fixed time interval, the problem of finding the minimum number of radar measurements required to satisfy the position estimation error constraint is solved. A closed-form solution for the optimum schedule is given in the case where the number of pulses is equal to the minimum number of pulses. For cases where one extra pulse is available, a solution method is described and an algorithm is derived.     

Upgrading conical scan with off-boresight measurements

Adding off-boresight measurements to a conical scan radar can bring the angle accuracy closer to the theoretical attainable limit. A model for off-boresight measurement implementation and its performances are discussed. The expected accuracy is calculated and compared with the Cramer-Rao bound. The model is also used to determine bias error induced by the target dynamics.     

Optimum Windows for Image Registration

Two-dimensional cross-correlation techniques are applied to the problem of image registration under the assumption of small geometric distortion. Optimum window functions are derived for two performance measures of interest: peak-to-sidelobe ratio and mean-square registration error. The latter is examined in terms of the contribution caused by noise and the contribution caused by geometric distortion. A generalized Lagrange multiplier approach is used to derive approximate solutions assuming random images. The case of Gaussian autocorrelation functions is examined in detail. Results of applying the theoretically derived window functions to real data are presented, showing significant improvement in correlator performance.     

基于IMU的机载TOPSAR目标定位方法

Burst工作模式和方位波束的主动扫描使得TOPSAR工作模式能够有效削弱ScanSAR模式的扇贝效应,同时也导致图像方位向像素位置与回波脉冲的关系变得复杂,给目标定位带来了很多问题。惯性测量单元(IMU)数据记录延时也会导致方位向定位误差存在,精确估计这个误差能够大大提高目标的方位向定位精度。从TOPSAR数据采集的几何关系和成像过程出发,结合机载IMU数据,提出了一种新的机载TOPSAR目标定位方法。该方法能够直接从TOPSAR斜距图像中获取目标的经纬度信息。通过实际飞行试验获取的机载TOPSAR数据验证了该方法的有效性,能够获取25 m的平均定位精度。     

Maximum likelihood angle extractor for two closely spaced targets

In a scenario of closely spaced targets special attention has to be paid to radar signal processing. We present an advanced processing technique, which uses the maximum likelihood (ML) criterion to extract from a monopulse radar separate angle measurements for unresolved targets. This processing results in a significant improvement, in terms of measurement error standard deviations, over angle estimators using the monopulse ratio. Algorithms are developed for Swerling I as well as Swerling III models of radar cross section (RCS) fluctuations. The accuracy of the results is compared with the Cramer Rao lower bound (CRLB) and also to the monopulse ratio technique. A novel technique to detect the presence of two unresolved targets is also discussed. The performance of the ML estimator was evaluated in a benchmark scenario of closely spaced targets - closer than half power beamwidth of a monopulse radar. The interacting multiple model probabilistic data association (IMMPDA) track estimator was used in conjunction with the ML angle extractor     

Robust space-time adaptive processing for airborne radar in nonhomogeneous clutter environments

Space-time adaptive processing (STAP) holds tremendous potential for the new generation airborne surveillance radar, in which the phased array antennas and pulse Doppler processing mode are adopted. A new STAP approach using the multiple-beam and multiple Doppler channels is presented here for airborne phased array radar. The approach with space-time multiple-beam (STMB) architecture is robust to array errors and has very low system degrees of freedom (DOFs). Hence, it has low sample support requirement and it is very suitable for the practical planar phased array radar under nonhomogeneous clutter environments. Meanwhile, a new nonhomogeneous detector (NHD) based on the correlation dimension (CD) is also proposed here, which is used as an effective method to screen tracing data prior to detection processing. It can further improve the performance of the STAP approach in the severely nonhomogeneous clutter environments. Therefore, a scheme that incorporates the correlation dimension nonhomogeneity detector (CD-NHD) with the STMB is recommended, which we term CD-NHD-STMB. The experimental simulation results indicate that: 1) the STMB processor is robust to array element error and has high performance under nonhomogeneous clutter environments; 2) the CD-NHD is also effective on the nonhomogeneous clutter. As a result, the CD-NHD-STMB scheme is robust to array element error and nonhomogeneous clutter, and therefore available for airborne phased array radar applications.     

Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications