Optimal Digital Beam Splitting for Radar Beacon Systems

Beam splitting for a radar beacon system that scans in azimuth is investigated from a theoretical viewpoint. The video output is quantized into two levels corresponding to a detection and no detection. Further, the antenna sensitivity profile is described by sin ?/?. For this system, a digital method of beam splitting that minimizes angular error is developed. Prior information about the probable location of targets can be included. Both Bayesian and minimax approaches are developed. The minimax estimate of the target azimuth is the average of the angles at which beacon signals are detected. The antenna beam can be interpolated by a factor of 10 when the signal power is 3 dB above the noise and without prior azimuth information The interaction of beam splitting and detection is discussed.     

Synthetic Aperture Radar

The general theory of side-looking synthetic aperture radar systems is developed. A simple circuit-theory model is developed; the geometry of the system determines the nature of the prefilter and the receiver (or processor) is the postfilter. The complex distributed reflectivity density appears as the input, and receiver noise is first considered as the interference which limits performance. Analysis and optimization are carried out for three performance criteria (resolution, signal-to-noise ratio, and least squares estimation of the target field). The optimum synthetic aperture length is derived in terms of the noise level and average transmitted power. Range-Doppler ambiguity limitations and optical processing are discussed briefly. The synthetic aperture concept for rotating target fields is described. It is observed that, for a physical aperture, a side-looking radar, and a rotating target field, the azimuth resolution is ?/? where ? is the change in aspect angle over which the target field is viewed, The effects of phase errors on azimuth resolution are derived in terms of the power density spectrum of the derivative of the phase errors and the performance in the absence of phase errors.     

Bias compensation and tracking with monopulse radars in the presence of multi path

The problem of tracking targets in the presence of reflections from sea or ground is addressed. Both types of reflections (specular and diffuse) are considered. Specular reflection causes large peak errors followed by an approximately constant bias in the monopulse ratio, while diffuse reflection has random variations which on the average generate a bias in the monopulse ratio. Expressions for the average error (bias) in the monopulse ratio due to specular and diffuse reflections and the corresponding variance in the presence of noise in the radar channels are derived. A maximum maneuver-based filter and a multiple model estimator are used for tracking. Simulation results for five scenarios, typical of sea skimmers, with Swerling III fluctuating radar cross sections (RCSs) indicate the significance and efficiency of the technique developed in this paper-a 65% reduction of the rms error in the target height estimate.     

一种改进的直方图概率多假设多目标跟踪方法

直方图概率多假设跟踪（H-PMHT）方法及其变形泊松分布直方图概率多假设跟踪（P-HPMHT）方法的一个主要缺点是其量测模型仅考虑了背景杂波而没有考虑传感器噪声,从而导致在低信噪比条件下检测概率较低。针对这一问题,提出了一种带传感器噪声模型的H-PMHT方法,通过将传感器噪声引入量测模型,从而明显提高了对低信噪比目标的跟踪检测能力。该方法的计算量与目标数保持线性关系,仍然适用于目标数目较多的情况。仿真实验表明：该方法在误跟踪比率为1‰,信噪比为6 dB时,检测比率可提升近20%,信噪比为3 dB时,可提升近10%。     

Effects of two-way decorrelation on radar detection inscintillation

A 3 dB gain in average signal-to-noise ratio of a monostatic radar operating in scintillation has recently been established both theoretically and observationally. The statistics of two-way scintillation are derived here for the case where the uplink and downlink both experience Rayleigh fading and where there is arbitrary correlation between the scintillation on the two paths. These statistics are then used to compute radar detection curves. A surprising result is obtained. The probability of detection is only weakly dependent (for P _D in the range 0.1 to 0.9) on the degree of uplink-downlink correlation in the scintillation when the average (nonfading) signal-to-noise ratio is constant and when proper account is taken of the change in mean power between the monostatic and bistatic cases. Much larger differences are seen in the detection curves with scintillation compared with nonfading curves (for P_D equal to 0.7 this scintillation loss is about 7 dB). Thus the difference in detection performance of monostatic and bistatic radars is determined primarily by the difference in the radar cross section (RCS) of the target for the two cases     

Distributed Array Radar

Distributed array radar (DAR) is a concept for efficiently accomplishing surveillance and tracking using coherently internetted mini-radars. They form a long baseline, very thinned array and are capable of very accurate location of targets. This paper describes the DAR concept. Factors involving two-way effective gain patterns for deterministic and random DAR arrays are analyzed and discussed. An analysis of factors affecting signal-to-noise ratio is presented and key technical and performance issues are briefly summarized.     

Classification of radar targets using synthetic neural networks

Radar target classification performance of neural networks is evaluated. Time-domain and frequency-domain target features are considered. The sensitivity of the neural network algorithm to changes in network topology and training noise level is examined. The problem of classifying radar targets at unknown aspect angles is considered. The performance of the neural network algorithms is compared with that of decision-theoretic classifiers. Neural networks can be effectively used as radar target classification algorithms with an expected performance within 10 dB (worst case) of the optimum classifier     

Multitarget detection using synthetic sampled aperture radars

A new multitarget detection technique using synthetic sampled aperture radar (SSAMAR) is presented. In contrast with the standard approach to multitarget detection, this technique may not require the use of phase shifting or tapering hardware. SSAMAR doubles the target pattern resolution, attenuates the sidelobes to about -27 dB, and significantly enhances the signal-to-noise ratio (SNR). Computer simulation is used to illustrate and validate this technique. Multitarget patterns for both standard and SSAMAR operations are provided     

Detection Probabilities for Log-Normally Distributed Signals

The amplitude and power of a large family of radio signals are observed to have log-normal probability density functions. Among these are signals propagated through random inhomogeneous media, a notable example being low frequency atmospheric radio noise. Of greater importance are certain radar targets that have been observed to have essentially log-normal density functions. Both ships and space vehicles may fall into this category. Curves of probability of detection vs. signal-to-noise ratio for the case of log-normal signals in Gaussian noise have been computed and are presented in this paper. The curves apply for square-law detection with varying degrees of postdetection linear integration. Both fully correlated and completely uncorrelated fluctuating signals are considered. It is shown that for log-normal signal distributions having large variances, the probability of detection differs significantly from that obtained using curves based on an assumed Rayleigh signal distribution.     

False alarm effects on estimation in multitarget trackers

An analysis of false alarm effects on tracking filter performance in multitarget track-while-scan radars, using variable correlation gates, is presented. The false alarms considered originate from noise, clutter, and crossing targets. The dimensions of the correlation gates are determined by filter prediction and measurement error variances. Track association is implanted either by means of a distance weighted average of the observations or by the nearest neighbor rule. State estimation is performed by means of a second-order discrete Kalman filter, taking into consideration random target maneuvers. Measurements are made in polar coordinates, while target dynamics are estimated in Cartesian coordinates, resulting in coupled linear filter equations. the effect of false alarms on the observation noise covariance matrix, and hence on state estimation errors, is analyzed. A computer simulation example, implementing radar target tracking with a variable correlation gate in the presence of false alarms, is discussed     

Effects of Navigation Errors in Maneuvering SAR

A maneuvering synthetic aperture radar in squint mode, during a loosely piloted maneuver, is simulated with presence of various navigation system errors. The error sources investigated place emphasis on short-term effects, involving platform servo transients, noise and quantization in accelerometers, interaction of angle pickoff uncertainty with the displacement from platform to radar antenna, and uncertainty in this displacement itself. Simulation results are accompained by interpretive discussion, and followed by suggested areas for further study.     

Quantitative SNR analysis for ISAR imaging using jointtime-frequency analysis-Short time Fourier transform

V.C. Chen recently presented an inverse synthetic aperture radar (ISAR) imaging technique using the joint time-frequency analysis (JTFA), which has been shown having a better performance for maneuvering targets over the conventional Fourier transform method. The main reason is because the frequencies of the radar returns of the maneuvering targets are time varying and a JTFA is a technique that is suitable for such signals, in particular a JTFA may concentrate a wideband signal, such as a chirp, while it spreads noise. We quantitatively study the signal-to-noise ratio (SNR) in the ISAR imaging using one of the typical JTFA techniques, namely the short time Fourier transform (STFT). We show that the SNR increases in the joint time-frequency (TF) domain over the one in the time or the frequency domain alone both theoretically and numerically. This quantitatively shows the advantage of the JTFA technique for the ISAR imaging     

Spectrum Distortion Due to Frequency Instabilities in a Two-Way Coherent Doppler Radar

The power spectral density of the intermediate frequency signal in a coherent Doppler navigation radar is derived. The effects of antenna parameters, periodic frequency instabilities, signal two-way transit time, and transmitter frequency modulation noise are considered Several examples based on the measured frequency modulation noise of a solid-state source transmitter are presented. The results indicate the degree of loss in signal-to-noise ratio, and spectrum broadening due to an increase in signal transit time and/or frequency modulation noise.     

High-Performance Weather Radar

A maser preamplifier designed into an X-band weather radar set AN/ MPS-34 increased the radar's sensitivity by 12.5 dB to an over-all 118.5 dBm. Many low-performance, obsoleted sets could be converted to a high-performance system through the inclusion of a maser. A qualitative discussion of the maser's operation is presented, and the quantitative effects of the maser low noise temperature on the radar's overall noise figure is derived. The meteorological targets not previously detectable are analyzed, and anticipated target detection is forecast.     

Faraday Loss for L-Band Radar and Communications Systems

The mechanism of Faraday rotation as it affects radar and communication propagation has been extensively treated (1, 7). The purpose of this paper is to point out the magnitude of the effect and its possible consequences which have not been appreciated. Contrary to what many believe, the two-way Faraday rotation angle and loss can be large at L-band for ground-based, linearly polarized radar systems observing targets above the ionosphere. Similarly, the one-way Faraday rotation and loss for linearly polarized, ground-to-space pace communication links at comparable frequencies can be large. The magnitude of the rotation loss depends on the location of the radar or communication station in latitude and longitude, the condition of the ionosphere, and the elevation and azimuth angles of the target. For example, based on the total electron content in 1970 (a peak sunspot activity year) at L-band, a two-way Faraday rotation greater than 50°a loss greater than 3.8 dB is calculated to occur at 60° N, 70° W, 75 percent of the time between the hours of 10 A.M. and 4 P.M. for nine months, and 22 percent of the total time for the entire year, when looking toward the south magnetic pole at low elevation angles. For the same year this rotation and loss at 15°N, 150° is calculated to occur 48 percent of the total time when looking south at low elevation angles.     

A Suboptimum Rank Test for Nonparametric Radar Detection

The optimum rank detector structure, in the Neyman-Pearson sense and under Gaussian noise conditions, is approximated by a suboptimum structure that depends on an adjustable parameter. This new rank detector, which operates on radar video signal, includes other well-known detectors as particular cases. The asymptotic relative efficiency (ARE) of the proposed rank detector is computed, with its maximum value the ARE of the locally optimum rank detector (LORD). The detection probability versus signal-to-noise ratio, and the effects of interfering targets are also calculated by Monte-Carlo simulations for different parameter values.     

ISAR imaging using an emulated multistatic radar system

The use of a monostatic radar configuration limits the ability of an inverse synthetic aperture radar (ISAR) system to image targets in certain geometries. By employing multistatic geometries this limitation may be overcome. This paper discusses the emulation of multistatic geometries, via sea surface multipath reflections, using a monostatic system. This application capitalises on the advantages provided by both monostatic and bistatic systems. The possibility of obtaining ISAR images using these emulated multistatic radar configurations is first theoretically discussed and then verified using experimental results.     

Adaptive Radar Detection in Doubly Nonstationary Autoregressive Doppler Spread Clutter

The problem of adaptive radar detection in clutter which is nonstationary both in slow and fast time is addressed. Nonstationarity within a coherent processing interval (CPI) often precludes target detection because of the masking induced by Doppler spreading of the clutter. Across range bins (i.e., fast time), nonstationarity severely limits the amount of training data available to estimate the noise covariance matrix required for adaptive detection. Such difficult clutter conditions are not uncommon in complex multipath propagation conditions where path lengths can change abruptly in dynamic scenarios. To mitigate nonstationary Doppler spread clutter, an approximation to the generalized likelihood ratio test (GLRT) detector is presented wherein the CPI from the hypothesized target range is used for both clutter estimation and target detection. To overcome the lack of training data, a modified time-varying autoregressive (TVAR) model is assumed for the clutter return. In particular, maximum likelihood (ML) estimates of the TVAR parameters, computed from a single snapshot of data, are used in a GLRT for detecting stationary targets in possibly abruptly nonstationary clutter. The GLRT is compared with three alternative methods including a conceptually simpler ad hoc approach based on extrapolation of quasi-stationary data segments. Detection performance is assessed using simulated targets in both synthetically-generated and real radar clutter. Results suggest the proposed GLRT with TVAR clutter modeling can provide between 5–8 dB improvement in signal-to-clutter plus noise ratio (SCNR) when compared with the conventional methods.     

基于傅里叶变换的航迹对准关联算法

研究了在组网雷达存在系统误差情况下的目标航迹关联问题,理论分析了雷达系统误差对目标航迹的影响,并将该影响表示为目标航迹的旋转和平移量。在此基础上,提出了一种基于傅里叶变换的系统误差配准前航迹对准关联算法,该算法将组网雷达的航迹数据看做为一种整体信息,采用傅里叶变换理论来估计和补偿组网雷达目标航迹数据到融合中心航迹数据的相对旋转量和平移量,将雷达网中雷达上报的目标航迹数据对准到融合中心,从而不依赖于估计雷达网系统误差,实现了误差配准前的航迹准确关联,能够为后端的系统误差配准提供可靠的关联目标航迹数据。