Clutter and jammer multipath cancellation in airborne adaptiveradar

Airborne surveillance radars must detect and localize targets in diverse interference environments consisting of ground clutter, conventional jamming, and terrain scattered jammer multipath. Multidimensional adaptive filtering techniques have been proposed to adaptively cancel this interference. However, a detailed analysis that includes the effects of multipath nonstationarity has been elusive. This work addresses the nonstationary nature of the jammer multipath and its impact on clutter cancellation and target localization. It is shown that the weight updating needed to track this interference will also modulate sidelobe signals. At the very least, this complicates the localization of targets. At the worst, it also greatly complicates the rejection of clutter. Several techniques for improving cancellation of jammer multipath and clutter are proposed, including 1) weight vector interpolation, extrapolation, and updating; 2) filter architecture, constraint, and beamspace selection; 3) prefilters; 4) 3-D STAP architectures; and 5) multidimensional sidelobe target editing     

Low-Error Bearing Estimation in Shallow Water

The multipath effect due to sound propagation in shallow water causes bearing errors in horizontal line arrays for all angles different from broadside when conventional resolution methods like beamformer or maximum entropy method are used. Error-free bearing estimates can be achieved only by means of generalized power estimators which use a priori knowledge about the spatial channel statistics. This a priori knowledge is usually unknown. The method described makes use of a pilot source which transmits training signals in order to achieve an estimate for a suboptimum spatial signal covariance matrix which is used for field matching.     

Analysis of single-platform passive emitter location with terraindata

Frequency measurements made at a moving platform can be used to locate an emitter. An error ellipsoid analysis is used to compare the performance under three levels of a priori information on the emitter's altitude: (1) no knowledge, (2) terrain data, and (3) complete knowledge of the emitter's altitude. The analysis is performed for two simple platform paths that provide frequency measurements that are approximately time reversed versions of one another. When no a priori knowledge is available there is little difference between the performance when the platform maneuvers on a concave circular path or on a convex circular path and the performance depends very Little on the platform altitude. However, when some a priori altitude information is available the performance is markedly different on the two paths and is highly dependent on the platform altitude. Thus, this analysis provides the unexpected result that for seemingly similar platform paths, the performance can vary markedly when the emitter altitude is assumed known. Also, an interesting result is that for some cases it is possible to achieve better x-y accuracy when using terrain data than when the emitter's z location is known, because the terrain data provides terrain slope information. These cases are characterized in terms of the terrain slope at the emitter     

Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

Multipath Limitations on Low-Angle Radar Tracking

This paper investigates the problem of tracking targets at a low elevation angle in the presence of specular and diffuse multipath. Quantitative estimates are derived of the elevation angles, and hence, range, at which targets of specified height can be accurately tracked. A parametric approach is followed in which the long-standing uncertainty of how terrain forward-scatters at low grazing angles is recognized at the outset. Particular attention is given to the effects of target motion which permit rejection of multipath components falling outside the radar tracker's passband. The results are presented in a form which can be readily applied to a spectrum of radar trackers with differing requirements. The limited experimental ental data on the specular and diffuse scattering parameters for several generic types of terrain are applied to estimate the significance of multipath under different situations and to indicate specific areas in which additional experimental data are critically needed.     

Multipath interferometry technique for airborne array calibration

A new technique is developed to compensate multiple-wavelength distortion in airborne antenna arrays. This approach exploits the phase information in microwave reflections from arbitrary terrain. To handle reflections incident over a broad angle, a range-Doppler preprocessor is used in each element channel to resolve wavefronts incident simultaneously from different directions. The phase information for each direction of arrival is compared between elements and processed by optimal estimators to determine the phase corrections needed to compensate the distortion. To develop the estimators, a statistical model of the complex baseband terrain reflections is developed. This is in turn used to generate conditional probability densities involving the range Doppler observations and the parameters to be estimated. These densities are subsequently used to develop minimum variance and maximum likelihood estimators. The new estimators use additional information that has not been exploited by previous techniques and therefore provide enhanced performance     

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...     

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.     

Gating Functions for Multipath Mitigation in GNSS BOC Signals

A new multipath mitigation technique is proposed for binary offset carrier (BOC) signals in global navigation satellite systems (GNSS) using the concept of gating function originally conceived for the GPS coarse-acquisition (C/A) code. Specially-tailored pulses are utilized to diminish the number of false-lock points of the code discriminator response and to improve the multipath mitigation capability. The code loop includes only four real correlators (two extra correlators are required for the simplified bump-jumping algorithm with BOC(n,n) signals). Results obtained with BOC(n,n) and BOC(2n,n) signals show that this technique eliminates the multipath ranging errors for reflected rays with relative delays typically above twenty percent of the spreading code chip duration, thus comparing favorably with the conventional receiver correlation techniques.     

Geolocation of a known altitude object from TDOA and FDOA measurements

Most satellite systems for locating an object on Earth use only time difference of arrival (TDOA) measurements. When there are relative motions between an emitter and receivers, frequency difference of arrival (FDOA) measurements can be used as well. Often, the altitude of an object is known (it is zero, for example) or can be measured with an altimeter. Two sets of geolocation solutions are proposed which exploit the altitude constraint to improve the localization accuracy. One is for TDOAs alone and the other for the combination of TDOA and FDOA measurements. The additional complexity by imposing the constraint is a one-dimensional Newton's search and the rooting of a polynomial. The covariance matrices of the new estimators are derived under a small measurement noise assumption and shown to attain the constrained Cramer-Rao lower bound (CRLB). When there is a bias error in the assumed altitude, using the altitude constraint will introduce a bias to the solution. Since applying the constraint decreases the variance, there is a tradeoff between variance and bias in the mean square error (MSE). The maximum allowable altitude error such that the constraint solution will remain superior to the unconstraint is given. Simulation results are included to corroborate the theoretical development.     

北斗二号中AS信号多径抑制方法及性能分析

针对北斗二号系统中AS（Authorized Service,授权服务）采用的BPSK（10）、BOC（14,2）、BOC（15,2.5）信号,研究如何抑制多径效应对AS信号跟踪的影响,提高定位精度.对3种信号的自相关特性及功率谱密度进行比对,并在对基于码跟踪环的EML（Early Minus Late,早减迟）和HRC（High Resolution Correlator,高精度相关器）技术进行分析的基础上,将这2种技术用于北斗二号AS信号的多径抑制.仿真表明：EML和HRC均适用于北斗二号AS信号,采用EML时,对BOC（14,2）、BOC（15,2.5）的多径抑制性能优于对BPSK（10）的;采用HRC时,对BPSK（10）的多径抑制性能优于对BOC（14,2）、BOC（15,2.5）的;对于BPSK（10）,HRC较EML在误差包络面积上多径抑制性能提高约89.7％;对于BOC（14,2）、BOC（15,2.5）,HRC和EML多径抑制性能相当,而EML的计算量相对较小因而整体性能更优;通过减小相关器间隔和增大带宽,可提高多径抑制性能,对BPSK（10）的效果比对BOC（14,2）、BOC（15,2.5）的更为明显.     

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.     

Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD), this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA). Firstly, the geometry of the RLA is formulated and analysed. According to its geometry, the intercepted noncoherent signals in multiple interception intervals are modeled. Correspondingly, the MUltiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed. Secondly, the synchronous coherent pulse signals are individually considered and formulated. And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals. Besides, we also derive the constrained Cramér-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known. At last, computer simulations are included to examine the performance of the proposed approach. The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation. In addition, coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

Synchronized perturbation elimination and DOA estimation via signal selection mechanism and parallel deep capsule networks in multipath environment

State-of-the-art model-driven Direction-Of-Arrival (DOA) estimation methods for multipath signals face great challenges in practical application because of the dependence on the precise multipath model. In this paper, we introduce a framework, based on deep learning, for synchronizing perturbation auto-elimination with effective DOA estimation in multipath environment. Firstly, a signal selection mechanism is introduced to roughly locate specific signals to spatial subregion via frequency domain filters and compressive sensing-based method. Then, we set the mean of the correlation matrix’s row vectors as the input feature to construct the spatial spectrum by the corresponding single network within the parallel deep capsule networks. The proposed method enhances the generalization capability to untrained scenarios and the adaptability to non-ideal conditions, e.g., lower SNRs, smaller snapshots, unknown reflection coefficients and perturbational steering vectors, which make up for the defects of the previous model-driven methods. Simulations are carried out to demonstrate the superiority of the proposed method.     

Passive localization of frequency-agile radars from angle andfrequency measurements

It is well known that the position of a stationary radar can be estimated by a single moving observer from angle and/or frequency measurements taken passively at different points in its trajectory. Depending on the measurement set different localization methods result: the bearing method (BM), the frequency method (FM), and the combined method (CM). Previous studies analyze the three methods on the basis of constant emitter frequencies. However, radars with constant emitter frequencies are not realistic. Frequency drift and frequency hopping have to be taken into account. Therefore, to include radars the emitter model has been extended by drift and frequency hopping in this study, and the estimation methods have been reanalyzed. The effects of the model extensions become transparent in a parametric Cramer-Rao (CR) analysis. The results obtained in this way are confirmed by Monte Carlo simulations taking maximum likelihood (ML) as estimation procedure     

SNR-based multipath error correction for GPS differential phase

Carrier phase multipath is currently the limiting error source for high precision Global Positioning System (GPS) applications such as attitude determination and short baseline surveying. Multipath is the corruption of the direct GPS signal by one or more signals reflected from the local surroundings. Multipath reflections affect both the carrier phase measured by the receiver and signal-to-noise ratio (SNR). A technique is described which uses the SNR information to correct multipath errors in differential phase observations. The potential of the technique to reduce multipath to almost the level of receiver noise was demonstrated in simulations. The effectiveness on real data was demonstrated with controlled static experiments. Small errors remained, predominantly from high frequency multipath. The low frequency multipath was virtually eliminated. The remaining high frequency receiver noise can be easily removed by smoothing or Kalman filtering     

On-line Vehicle Motion Estimation from Visual Terrain Information Part II: Ground Velocity and Position Estimation

An algorithm, combining velocity/height estimates, obtained from an airborne body fixed image shift estimator with auxiliary on-board measurements and sparsely stored terrain profile information constitutes an entirely passive autonomous navigation system suitable for moderate-g flight missions. Two versions are addressed. The "naive estimator," in which altitude estimates are multiplied by velocity/height estimaters, yields ground velocity. Position, obtained by integration, diverges with time. The "extended Kalman filter" (EKF) version, in which velocity and position are defined as state space components, locks on the stored terrain profile and does not diverge with time. It degenerates into the "naive estimator" if the terrain is completely flat. Numerical examples indicate excellent performance potential of the EKF estimator.     

直达与非直达环境中的多目标解耦直接定位方法

针对直达（LOS）与非直达（NLOS）环境中的定位问题,提出了一种波形已知条件下的单阵地多目标直接定位（DPD）算法。该算法针对发射时间已知和未知两种情况,利用多径信号到达角度与时延关于障碍物（或反射体）、观测站与目标位置参数的数学关系,建立了三维目标位置的最大似然（ML）函数,无需估计测量参数,避免了传统两步定位方法所需的非直达径识别与数据关联。为了克服多目标定位中的高维非线性优化问题,该算法利用独立波形信息将多目标定位解耦为对各个目标单独求解。通过对目标函数有效近似,算法在发射时间已知和未知两种情况下均仅需三维网格搜索,比相应的两步定位方法具有更低的计算量。此外,基于多径定位场景,推导了发射时间已知和未知两种情况下的位置估计克拉美罗界（CRB）。仿真结果表明：算法的定位性能能够逼近相应的克拉美罗界,比传统两步定位方法和子空间直接定位算法具有更高的定位精度。     

An LMS Adaptive Array for Multipath Fading Reduction

Multipath fading often poses a serious hindrance in radiocommunication. The application of a least-mean-square (LMS)adaptive array to the problem of multipath fading reduction is discussed. However, it is known that multipath components are in general correlated with one another. We examine the effect of the correlation on the performance of the LMS adaptive array. When the correlation coefficient does not equal or approximate 1, the LMS adaptive array suppresses the multipath signals significantly by nulling. On the other hand, when the correlation coefficient nearly equals 1, the LMS adaptive array prevents the output signalpower from decreasing. Therefore, the LMS adaptive array mayreduce the multipath fading effectively for any correlation coefficient value. A reference signal in the LMS adaptive array is also discussed. It is shown that synchronization in the referencesignal generation must be extremely accurate. Moreover, aprocessor configuration is proposed which may generate thereference signal with the required accuracy.     

A Weighted Inner Product Estimator in the Geometric Algebra of Euclidean 3-Space for Source Localization Using an EM Vector-sensor

In this paper, the source localization by utilizing the measurements of a single electromagnetic (EM) vector-sensor is investigated in the framework of the geometric algebra of Euclidean 3-space. In order to describe the orthogonality among the electric and magnetic measurements, two multivectors of the geometric algebra of Euclidean 3-space (G3) are used to model the outputs of a spatially collocated EM vector-sensor. Two estimators for the wave propagation vector estimation are then formulated by the inner product between a vector and a bivector in the G3. Since the information used by the two estimators is different, a weighted inner product estimator is then proposed to fuse the two estimators together in the sense of the minimum mean square error (MMSE). Analytical results show that the statistical performances of the weighted inner product estimator are always better than its traditional cross product counterpart. The efficacy of the weighted inner product estimator and the correctness of the analytical predictions are demonstrated by simulation results.