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     

Monopulse DOA estimation of two unresolved Rayleigh targets

This paper provides for new approaches to the processing of unresolved measurements as two direction-of-arrival (DOA) measurements for tracking closely spaced targets rather than the conventional single DOA measurement of the centroid. The measurements of the two-closely spaced targets are merged when the target echoes are not resolved in angle, range, or radial velocity (i.e., Doppler processing). The conditional Cramer Rao lower bound (CRLB) is developed for the DOA estimation of two unresolved Rayleigh targets using a standard monopulse radar. Then the modified CRLB is used to give insight into the boresight pointing for monopulse DOA estimation of two unresolved targets. Monopulse processing is considered for DOA estimation of two unresolved Rayleigh targets with known or estimated relative radar cross section (RCS). The performance of the DOA estimator is studied via Monte Carlo simulations and compared with the modified CRLB     

Correlation between horizontal and vertical monopulse measurements

Many radar systems use the monopulse ratio to extract angle of arrival (AOA) measurements in both azimuth and elevation angles. The accuracies of each such measurement are reasonably well known: each measurement is, conditioned on the sum-signal return, Gaussian-distributed with calculable bias (relative to the true AOA), and variance. However, we note that the two monopulse ratios are functions of basic radar measurements that are not entirely independent, specifically in that the sum signal is common to both. The effect of this is that the monopulse ratios are dependent, and a simple explicit expression is given for their correlation; this is of considerable interest when the measurements are supplied to a tracking algorithm that requires a measurement covariance matrix. The system performance improvement when this is taken into account is quantified: while it makes little difference for a tracking radar with small pointing errors, there are more substantial gains when a target is allowed to stray within the beam, as with a rotating (track-while-scan) radar or when a single radar dwell interrogates two or more targets at different ranges. But in any case, the correct covariance expression is so simple that there is little reason not to use it. We additionally derive the Cramer-Rao lower bound (CRLB) on joint azimuth/elevation angle estimation and discover that it differs only slightly from the covariance matrix corresponding to the individual monopulse ratios. Hence, using the individual monopulse ratios and their simple joint accuracy expression is an adequate and quick approximation of the optimal maximum likelihood procedure for single resolved targets.     

Adaptive digital beamforming for angle estimation in jamming

A radar digital beamforming (DBF) architecture and processing algorithm is described for nulling the signal from a mainlobe electronic jammer and multiple sidelobe electronic jammers while maintaining monopulse angle estimation accuracy on the target. The architecture consists of a sidelobe jamming (SLJ) cancelling adaptive array (AA) followed by a mainlobe jamming (MLJ) canceller. A mainlobe maintenance (MLM) technique or constrained adaptation during the sidelobe cancellation process is imposed so that the results of the SLJ cancellation process do not distort the subsequent mainlobe cancellation process. The SLJ signals and the MLJ signals are thus cancelled sequentially in separate processes. This technique was developed for improving radar processing in determining the angular location of a target, and specifically for improving the monopulse technique by maintaining the accuracy of the target echo monopulse ratio in the presence of electronic jamming by adaptive suppression of the jamming signals before forming the monopulse sum and difference beams     

Statistical description of monopulse parameters for trackingRayleigh targets

The conditional probability density function (pdf) is developed for each monopulse measurement of a Rayleigh target by conditioning the pdf of the complex monopulse ratio on the measured amplitude of the sum signal. The conditional pdf is used to develop the conditional Cramer-Rao Lower Bound (CRLB) for any unbiased estimator of the direction-of-arrival (DOA). Conditional maximum likelihood (CML) and conditional method of moments (CMM) estimators of the DOA are developed along with estimates of the variances associated with the monopulse ratio and DOA estimate. Using simulation results, the performances of the CML and CMM estimators of the DOA are compared with the performance of standard monopulse ratio and the performances of the variance estimators are also studied     

Angle Estimation with Adaptive Arrays in External Noise Fields

A method of estimating the angle of arrival of a signal at an array of sensors in an external noise environment is outlined. The development is based on a maximum likelihood estimator and leads naturally to adaptive sum and difference beams which null the external noise sources. An algorithm for estimating angle of arrival, based on the outputs of adaptively distorted sum and differnce beams, is shown to perform well in the presence of sidelobe and/or main beam interference.     

机载雷达中的单脉冲技术

 本文总结机载雷达中单脉冲技术的研究和应用,着重讨论幅度比较系统的关键技术,给出有关数据。 机载雷达中的单脉冲技术着眼于抗干扰性能和特殊应用。这些应用包括空对地测距、角分辨力改进、地形防撞。本文阐述了这些特殊应用。     

An Application of Radiometric Techniques to Precision Angle Tracking Radar Systems

A new technique is described which provides for precision angle tracking of celestial radio sources with a conventional monopulse antenna receiving system. It is shown that this technique is readily adapted to angle tracking radars. The features of conventional monopulse operation are preserved while permitting precise angle tracking of noise sources when signal to noise ratios are much less than unity. Measurements, using a four-horn monopulse feed with a 28-foot parabolic reflector and a "monopulse radiometer" produced the characteristic monopulse angle detection functions when using the sun, the moon, and Cassiopeia A as boresight reference sources. Precision measurements were made to 8 arc second under varying weather conditions using 28-foot radio astronomy antennas. The accuracy of the measurements were limited by the antenna angle encoders, consequently no conclusions are drawn with regard to the absolute accuracy of the measurements. The celestial coordinates of four discrete radio sources and the equations for coordinate transformation to local elevation and azimuth are contained in the Appendixes.     

Specification and Performance of Passive Sonar Spectral Estimators

The application of existing estimation theory to the problem of specification and performance of passive sonar spectral estimators is considered. The classification function is addressed, so that the signal is assumed to be present, and so that the energy arrival angle is known. The spatial filter considered is a line array of M equally spaced omnidirectional hydrophones. Signal and ambient noise are both zero-mean, wide-sense, stationary Gaussian random processes that differ in their spatial correlation across the face of the array. The signal is a plane wave that can be made totally spacially corrected between array elements by inserting delays between sensors to invert the signal propagation delay. The noise correlation is a function of frequency, bandwidth, element separation, and the relative time delay between sensors. Under these assumptions, the Cramer-Rao lower bound is derived for the class of unbiased estimates of signal power in a narrow frequency band at the hydrophone in the presence of correlated ambient noise of known power. The bound is examined numerically, resulting in a threshold phenomenon with M that constitutes a new design consideration. In addition, there is a striking insensitivity to realistic values of ambient noise correlation, and there are ranges in signal-to-noise ratio for which one gains more by increasing M than by increasing the bandwidth-time product. Specific processors, including a new unbiased estimator when noise power is unknown, are developed.     

Radar measurement extraction in the presence of sea-surface multipath

In the presence of sea-surface multipath monopulse radar signals from a low elevation target have three alternative paths in addition to the direct (radar-to-target) path due to reflections from the sea surface. The specular reflection causes significant signal fading. The diffuse reflection causes an approximately constant bias to the in-phase component of the monopulse ratio, which is the standard extractor of the direction of arrival (DOA) in the monopulse processing. The diffuse reflection also causes higher standard deviation to the in-phase component of the monopulse ratio. We propose a maximum likelihood (ML) angle extraction technique for low elevation targets of known average signal strength having a Rayleigh fluctuation. The results show that this method reduces the error of the estimated angle compared with the conventional monopulse ratio estimator. Subsequently, the ML angle extractor is modified for the unknown average signal strength case. This modified angle extractor has only a small performance degradation compared with the known average signal strength case, but it performs much better than the monopulse ratio based estimator. An algorithm to calculate the accuracy of the estimated angle (or height) is also presented. This angle extractor reduces the root-mean-square error (RMSE) by more than 50% in the signal processing stage when used in a low flying target tracking scenario. The same algorithm can be used to track sea skimmers.     

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.     

Estimating the Angles of Arrival of Multiple Plane Waves

The problem of estimating the angles of arrival of M plane waves incident simultaneously on a line array with L + 1 (L?M) sensors utilizing the special eigenstructure of the covariance matrix C of the signal plus noise at the output of the array is addressed. A polynomial D(z) with special properties is constructed from the eigenvectors of C, the zeros of which give estimates of the angle of arrival. Although the procedure turns out to be essentially the same as that developed by Reddi, the development presented here provides insight into the estimation problem.     

反向交叉眼对单脉冲雷达干扰效果分析及仿真验证

交叉眼干扰被认为是对单脉冲雷达干扰最有效的方式之一。基于雷达方程建立了隔离平台回波下的两点源反向交叉眼干扰模型，推导了交叉眼干扰欺骗角一般性公式，研究了干扰机发射天线间距、干扰平台旋转角和干扰机相对雷达之间距离等参数变化对角度欺骗效果的影响，并依据单脉冲雷达接收机获取角度的信息处理流程，建立了单脉冲雷达接收机仿真模型，对交叉眼数学模型的正确性和局限性进行了分析。研究结果表明：单脉冲雷达越靠近两点源交叉眼干扰机中心线、干扰机两发射天线间距越大、与干扰机距离越近时，角度欺骗效果越好；单脉冲雷达的欺骗角度随着与干扰机距离的接近呈指数式增大；数学模型和仿真模型计算的单脉冲雷达角度误差最大值随干扰机天线与雷达天线中心连线的夹角的增大呈指数化增长。研究可为交叉眼干扰工程设计作参考。     

Variance Analysis of the Angle Output Voltage for an Amplitude Monopulse Receiver

The amplitude-comparison monopulse receiver utilizes two overlapping antenna patterns to determine the angle of arrival of an incoming RF signal for use in a direction-finding application. The thermal noise introduced by the receiver distorts the signal, causing an error in determining the exact angle of arrival of the signal. The analysis derives an expression for the deviation of the angle output voltage, or the angular error, due to receiver noise as a function of 1) the angle of arrival and 2) the signal-to-noise ratios of the two channels of the receiver. A receiver using a square-law detector and one using a linear detector are analyzed.     

比相单脉冲雷达测角与角闪烁研究

比相单脉冲雷达采用和差通道接收信号比相的方法测角。一般认为,雷达事实上并不是在测量目标的方向,而是在测量目标的角闪烁方向。从特殊的两点目标出发,分析了单点目标和复杂目标下比相单脉冲雷达和差通道方式测角的原理与内在异同,探讨了比相单脉冲雷达测角与角闪烁的关系,提出有关雷达测角的新的观点。     

与空时二维自适应滤波兼容的单脉冲测角新方法

针对机载相控阵雷达系统提出了一种空时二维自适应单脉冲测角方法 ,当存在阵元和通道幅相误差时它仍具有较高的测角精度。还给出了一种稳健的自适应和、差波束增益归一化方法 ,并讨论了所提方法的简化兼容实现方案。最后给出了基于高保真雷达杂波模拟数据的仿真实验结果     

Model-based multifrequency array signal processing for low-angletracking

Tracking low-altitude targets over the sea is problematic because of interference between the direct and reflected signal. Standard monopulse trackers can experience large errors because of multipath maximum likelihood estimation (MLE) has been used to more accurately estimate the target height in the presence of multipath MLE is a model-fitting technique where the model parameters are chosen to maximize the likelihood function. It is shown that the type of observation model has a large effect on performance. Tracking performance is compared using three different observation models employing varying amounts of a priori information. Results are presented for different array sizes: eight and 32-element arrays and two-element subarrays typical of phase monopulse. Performance is compared with that of standard techniques such as Fourier beamforming and phase monopulse     

Radar Performance with Multipath Using the Complex Angle

The complex angle (CA) method for resolving a low angle target from its multipath signal is evaluated in the presence of system noise. It is shown that standard deviation improvements of around 3-to-1 can be achieved at a 20-dB signal-to-noise power ratio relative to a normal monopulse system without the CA. It is also shown that the CA method is unbiased, giving bias improvements of as much as 100 times relative to normal monopulse. Evaluation of the assumptions in the technique shows very little sensitivity to knowledge of the reflecting surface's conductivity or dielectric constant. However, the method is somewhat sensitive to knowledge of surface roughness.     

Angle estimation for two unresolved targets with monopulse radar

Most present-day radar systems use monopulse techniques to extract angular measurements of sunbeam accuracy. The familiar "monopulse ratio" is a very effective means to derive the angle of a single target within a radar beam. For the simultaneous estimation of the angles of two closely-spaced targets, a modification on the monopulse ratio was derived in (Blair and Pearce, 2001), while (Sinha et al., 2002) presented a maximum likelihood (ML) technique via numerical search. In this paper it is shown that the ML solution can in fact be found explicitly, and the numerical search of ((Sinha et al., 2002) is unnecessary. However, the ML solution requires the signal to noise ratio (SNR) for each target to be known, and hence we generalize it so it requires only the relative SNR. Several versions of expectation maximization (EM) joint angle estimators are also derived, these differing in the degree to which prior information on SNR and on beam pattern are assumed. The performances of the different direction-of-arrival (DOA) estimators for unresolved targets are studied via Monte Carlo, and it is found that most have similar performance: this is remarkable since the use of prior information (SNR, relative SNR, beam pattern) varies widely between them. There is, however, considerable performance variability as a function of the two targets' off-boresight angles. A simple combined technique that fuses the results from different approaches is thus proposed, and it performs well uniformly.     

Acoustic node calibration using a moving source

Acoustic nodes, each containing an array of microphones, can track targets in x-y space from their received acoustic signals, if the node positions and orientations are known exactly. However, it is not always possible to deploy the nodes precisely, so a calibration phase is needed to estimate the position and the orientation of each node before doing any tracking or localization. An acoustic node can be calibrated from sources of opportunity such as beacons or a moving source. We derive and compare several calibration methods for the case where the node can hear a moving source whose position can be reported back to the node. Since calibration from a moving source is, in effect, the dual of a tracking problem; methods derived for acoustic target trackers are used to obtain robust and high resolution acoustic calibration processes. For example, two direction-of-arrival-based calibration methods can be formulated based on combining angle estimates, geometry, and the motion dynamics of the moving source. In addition, a maximum likelihood (ML) solution is presented using a narrowband acoustic observation model, along with a Newton-based search algorithm that speeds up the calculation the likelihood surface. The Cramer-Rao lower bound (CRLB) on the node position estimates is also derived to show that the effect of position errors for the moving source on the estimated node position is much less severe than the variance in angle estimates from the microphone array. The performance of the calibration algorithms is demonstrated on synthetic and field data.