Emitter localization using clustering-based bearing association

A closed-form emitter location estimator using time difference of arrival (TDOA) measurements is developed based on triangulation of hyperbolic asymptotes. The problem of associating the asymptotes with the emitter is solved by clustering the bearing angles of the linear asymptotes using a kernel density estimate. A closed-form estimate of the emitter location is obtained from triangulation of the clustered bearings using a weighted version of the pseudolinear estimator. By way of simulation examples, the proposed closed-form estimator is shown to outperform the computationally demanding and divergence-prone maximum likelihood (ML) estimator at moderate TDOA noise levels.     

存在观测站位置误差的转发式时差无源定位

无源定位中,由于观测站安放在运动平台等原因造成的观测站位置误差会影响无源定位精度性能。另外到达时间差(简称时差)(TDOA)的转发式测量需要将不同观测站截获到的辐射源信号都转发到同一位置,如主观测站。针对这两个问题,提出了基于约束总体最小二乘(CTLS)的无源定位算法。首先将转发式时差的非线性定位方程转化为不需要中间变量的直接线性方程,再基于CTLS算法依次转化为约束优化问题和无约束优化问题,最后推导给出定位近似闭式解。仿真实验表明在观测站误差较大时,该算法与其他算法相比定位精度性能较好。     

姿态抖动运动单平台LBI无源定位系统的角变化率估计和定位算法研究

 研究了采用长基线干涉仪(LBI)体制的运动单平台无源定位系统受平台姿态抖动影响的问题,指出由于平台姿态的快速无规则变化,相位差变化率(RPDC)方法将难以适用,应当采用目标方位角变化率参数进行定位。基于此,针对三维几何空间,提出了一种RP-LS方法估计目标方位角变化率,继而实现对目标的定位。仿真结果表明,该方法能有效解决LBI体制运动单平台定位系统对姿态抖动的适应问题,实现对目标的快速高精度定位。     

PASSIVE LOCATION AND ACCURACY ANALYSIS USING TDOA INFORMATION OF MULTI-STATIONS

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Passive localization by a single moving observer using TOA only with unknown SRI: Observability analysis and algorithm

Passive localization by a single moving observer using Time of Arrival (TOA) only with an unknown Signal Repetition Interval (SRI) is investigated in this paper. Observability analysis is performed first. The observability condition for uniquely determining the emitter position and SRI is derived. The conditional Cramer-Rao Lower Bound (CRLB) is also analyzed. It is found that the ambiguity of the SRI integer of the first TOA does not affect the theoretical estimation precision of the emitter position and SRI. A Reference-Fixed Differential TOA (RFDTOA)-based Iterative Maximum Likelihood Estimator (IMLE) is proposed, which only needs O(M) computational operations. Theoretical analysis and simulation results show that the Mean Square Error (MSE) of the proposed algorithm could attain the CRLB with moderate Gaussian measurement noise.     

Omega Lane Ambiguity Resolution Using Methods of Statistical Decision Theory

Lane ambiguity is an inherent problem of navigation systems using phase measurements. A lane ambiguity resolution technique combining methods of hyperbolic and range-range modes of navigation has been developed. The basis of this approach is that the ensemble of received phases at any location forms a unique set and therefore the lane resolution problem reduces to finding a position such that the expected set of phases (or the phase predicted for the position of the navigator) matches the received set. This method of lane resolution is not constrained by lane widths and using the phase data of 10.2, 13.6, and 11? kHz; lane resolution has been accomplished for distances of up to 120 nmi. This method of lane resolution requires phase data from at least four stations at any frequency and is very sensitive to uncompensated propagation phase shifts.     

A new method for finding electromagnetic emitter location

The position of a source of radiation is often obtained from bearing data, taken over an interval of time, and combining it with navigation data. A new method using total least squares (TLS) has been suggested for the accurate estimation of an emitter location when bearing observation errors are random. Further, an iterative two-stage approach involving TLS and Kalman filtering is developed for accurate estimation of the emitter location when bearing observation errors are an algebraic sum of random and systematic errors. The elegance and efficacy of the proposed methods are illustrated through digital computer simulated examples     

传感器位置误差条件下的约束总体最小二乘时差定位算法

 现代定位系统中,传感器往往被安放在运动平台上,其位置无法精确得知,存在估计误差,将严重影响对目标的定位精度。针对这一问题,提出基于约束总体最小二乘(CTLS)的到达时差(TDOA)定位算法。首先通过引入中间变量,将非线性TDOA定位方程转化为伪线性方程,再利用CTLS技术,全面考虑伪线性方程所有系数中的噪声。在此基础上推导了定位方程的目标函数,再根据牛顿迭代方法,进行数值迭代,快速得到精确解。采用一阶小噪声扰动分析方法,对该算法的理论性能进行了分析,证明了算法的无偏性和逼近克拉美-罗下限(CRLB)。仿真实验表明,该算法克服了现有总体最小二乘(TLS)算法不能达到CRLB、两步加权最小二乘(two-step WLS)算法在较高噪声时性能发散的缺陷,在较高噪声时定位精度仍然能达到CRLB。     

惯性/里程计组合导航无地标行进中自主对准

载车行进中自主对准可有效缩短机动前准备时间,提高姿态对准精度以及对准过程中无地标自主定位精度是关键。本文提出一种里程计辅助捷联惯导系统行进中对准算法,推导了行进中精对准滤波模型以及对准过程中无地标自主定位算法。为缩短对准时间、减小由于航向角误差未收敛时造成的定位误差,利用回溯法将粗对准过程存储数据用于精对准过程,且回溯法仅需存储少量数据适合于工程应用。车载实测数据分析表明算法可同时实现行进中自主对准与对准过程中无地标自主定位,有效提高了载车快速机动能力,航向角对准精度优于1 mil,对准过程中无地标自主定位精度优于0.3%行程。     

A New Approach to Geometry of Range Difference Location

Loran, as an example of a ?hyperbolic? range difference location system, provides hyperbolic lines of position on which the target must lie. It is shown in this paper that lines of position need not be hyperbolic, i.e., an exact straight line of position on the plane or the surface of a sphere (where the solution is a great circle) is derived and computer-generated error maps are given.     

Scan-based emitter passive localization

This paper investigates the problem of estimating the position of a scanning emitter using a passive scan-based geolocation technique. This is achieved by taking advantage of the geometric constraints introduced by the uniform rotating motion of the antenna main beam as it sweeps across a number of separate receivers. A detailed analysis of the estimation process and accuracy of the emitter position is given and a number of computer simulations showing the benefits of this geolocation technique are also included     

基于3DT的空时自适应单脉冲参数估计算法

空时自适应处理(STAP)是机载预警雷达抑制杂波和干扰的一项关键技术,而多普勒三通道联合自适应处理(3DT)是适合工程实现的降维(RD)STAP方法。STAP目标检测后还需进一步估计目标的角度参数,因此将自适应单脉冲(AM)技术引入3DT,提出了一种高精度联合估计目标速度与方位空间角的空时自适应单脉冲算法。理论分析与仿真实验结果表明,当目标多普勒频率偏离检测多普勒单元中心频率时,该算法能同时减少目标多普勒跨越损失和空时导引矢量失配损失,进而提高输出信杂噪比(SCNR),改善目标测角精度。     

ANALYSIS OF LOCATION ACCURACY FOR AN EMITTER USING SATELLITE- MOUNTED INTERFEROMETER

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Moving scanning emitter tracking by a single observer using time of interception: Observability analysis and algorithm

The target motion analysis (TMA) for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception (TOI) measurements only is investigated in this paper.By transforming the TOI of multiple scan cycles into the direction difference of arrival (DDOA) model,the observability analysis for the TMA problem is performed.Some necessary conditions for uniquely identifying the scanning emitter trajectory are obtained.This paper also proposes a weighted instrumental variable (WIV) estimator for the scanning emitter TMA,which does not require any initial solution guess and is closed-form and computationally attractive.More importantly,simulations show that the proposed algorithm can provide estimation mean square error close to the Cramer-Rao lower bound (CRLB) at moderate noise levels with significantly lower estimation bias than the conventional pseudo-linear least square (PLS) estimator.     

基于OTHR与纯角度传感器群数据关联的模式辨识与定位精度提升

 天波超视距雷达(OTHR)目标跟踪面临着"三低"(低检测概率、低数据率和低测量精度)和"多径"(多条传播路径)的挑战,因此传播模式的准确辨识与目标定位精度提升是改善跟踪能力的关键。首先利用纯角度传感器群获得目标地理位置的初步估计,然后采用极大似然估计建立了OTHR的传播模式和杂波模式的辨识规则,进而利用最小方差估计准则实现OTHR和纯角度传感器群的量测融合。仿真结果表明,此算法的模式辨识正确率很高,能明显提升方位角的测量精度,但是不能明显提升径向距的精度。     

斜下降旋翼桨涡干扰声源定位及表面压力

旋翼桨-涡干扰（BVI）是直升机在进场和离场等近地飞行时后行桨叶切割前行桨叶脱落桨尖涡产生的气动扰动，该扰动不仅对桨叶表面压力载荷产生激励作用，同时也会引起旋翼噪声出现激增，旋翼噪声激增的主要成分为桨-涡干扰噪声。本文首先对斜下降桨-涡干扰状态桨叶表面载荷进行数值计算；然后分别阐述了基于改进整周期同步平均旋翼噪声去噪方法、基于多层小波包分解的桨-涡干扰声源识别和分离方法以及基于bartlett时延计算和球面插值的声源定位方法，设计并开展了风洞斜下降状态桨-涡干扰桨叶表面压力和声源定位试验，给出了开发的声源定位软件界面、声源定位图像畸变校准方法及声阵列现场校准方法；最后对比分析了不同试验状态的桨-涡干扰噪声声源特性以及和桨叶表面压力之间的关联性，并给出了声源定位及表面压力试验数据分析结果。结果表明典型斜下降状态后行侧桨-涡干扰主要出现在方位角310°~330°、径向位置1.6~1.8 m桨盘平面区域。     

Uncertainty ellipses and their application to interval estimation of emitter position

A method of interval estimation of position of an object emitting electromagnetic energy is presented. The problem is considered in cases of known and unknown errors of emitter position determination. Precise expressions concerning two-dimensional confidence regions for unknown position of the emitter have been obtained. Uncertainty regions defined as error ellipses and confidence ellipses have been determined. Qualitative and quantitative comparison of considered regions have been made. The presented approach and obtained results may be useful in electronic intelligence (ELINT) and electronic warfare (EW) applications, in radio navigation, ballistics, and in rescue operations at sea as well.     

Aperture error mitigation via local-state estimation for frequency-based emitter location

This paper considers the problem of locating a stationary coherent emitter via a single moving platform making frequency measurements in the presence of aperture state uncertainty. It is shown that the estimated emitter location is most sensitive to the receiving aperture velocity uncertainty. The required aperture velocity accuracy is determined through a noninfinitesimal perturbation analysis. A solution to location accuracy enhancement with a minimal hardware addition is attempted. It is shown that this can be achieved by mounting a high-resolution tri-axis microelectromechanical systems (MEMS) accelerometer at the aperture to measure its velocity, which can deviate significantly from that estimated by the on-board navigation system. The Doppler shifts of the GPS signal carrier frequency, whenever it can be acquired through the aperture, are also considered as a way to aid the aperture velocity measurement. A decentralized, federated processing method for the aperture velocity estimate referenced at the aperture, integrating all measurement data, is presented. An upper bound for the error of aperture velocity estimate is derived. The potential for significant accuracy enhancement for emitter location is demonstrated.     

基于短时时差序列的无源定位方法

针对脉冲辐射源定位问题,提出了一种基于短时时差(TDOA)序列的多站无源定位新方法.首先建立了TDoA序列模型,然后推导了该方法定位误差的克拉美罗下限(CRLB),并提出了一种高效的解算方法--两步定位法(TSLM):第1步利用TDOA序列线性估计出TDOA及其变化率信息,第2步基于TDOA及其变化率信息进行定位.典型...     

包含乘性噪声自适应修正的非合作目标相对导航算法

无人机（UAV）态势感知的任务是利用机载传感器对未知环境进行目标识别和引导,针对无人机与非合作目标间中远距离的相对导航问题,提出了一种基于角度和距离量测的相对状态估计算法。在现有滤波算法的基础上,为了提高精度和稳定性,本文利用了列文伯格-马夸尔特（LM）优化的思想对迭代卡尔曼滤波（IEKF）算法进行改进,提出了一种LM-IEKF算法,并推导该算法在迭代过程中的状态更新方程及协方差阵的递推公式。在此基础上,考虑到距离传感器由于信号相关特性而引入的乘性噪声,现有的加性噪声模型难以适应,因此,进一步提出了基于量测噪声自适应修正的Modified LM-IEKF方法,通过在线实时更新噪声阵提高滤波的精度,并设置渐消记忆指数平滑估计结果。算法验证结果表明,与现有的EKF、IEKF算法相比,在仅含加性噪声的情况下,LM-IEKF算法具有更好的性能;在包含乘性噪声的情况下,Modified LM-IEKF可以有效地估计量测噪声,与目前广泛使用的EKF算法相比,在综合相对位置和相对速度精度上分别提高了10%和23%。