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.     

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     

Adaptive Maximum Likelihood Receiver for Direct-Ranging Applications

Recent interest in direct-ranging navigation methods has prompted new research into practical receiver structures which provide improved signal processing. Maximum likelihood receivers are compared with conventional phase-locked receivers by theoretical and simulation methods as phase estimators based on signal measurements only. Signal-to-noise ratio (SNR) enhancement is examined and filter recommendations made. An adaptive maximum likelihood receiver is then developed which uses both signal measurements and a priori data to improve phase estimation accuracy. Simulation results indicate a 33.3 dB processing gain yielding a ranging error standard deviation of ±15 feet for zero dB received SNR. Nonadaptive and adaptive receivers are fabricated, flight tested, and experimental results reported.     

Estimation techniques for GMSK using linear detectors in satellite communications

This paper describes data-aided signal level and noise variance estimators for Gaussian minimum shift keying (GMSK) when the observations are limited to the output of a filter matched to the first pulse-amplitude modulation (PAM) pulse in the equivalent PAM representation. The estimators are based on the maximum likelihood (ML) principle and assume burst-mode transmission with known timing and a block of L₀ known bits. While it is well known that ML estimators are asymptotically unbiased and efficient, the analysis quantifies the rate at which the estimators approach these asymptotic properties. It is shown that the carrier phase, amplitude, and noise variance estimators are unbiased and can achieve their corresponding Cramer-Rao bounds with modest combinations of signal-to-noise ratio and observation length. The estimates are used to estimate the signal-to-noise ratio. It is shown that the mean squared error performance of the ratio increases with signal-to-noise ratio while the mean squared error performance of the ratio in decibels decreases with signal-to-noise ratio. Simulation results are provided to confirm the accuracy of the analytic results.     

Passive localization of moving emitters using out-of-planemultipath

The purpose of this work is to establish how a moving emitter, such as a jammer, can be localized by a passive receiver through the use of out-of-plane multipath signals reflected by the terrain. This is a novel localization technique that assumes no a priori knowledge of the localization of the multipath sources. The emitter parameters of range, heading, velocity, and altitude are estimated by exploiting the correlation between the direct-path signal and the delayed and Doppler modulated signals. Two basis assumptions about the scattering properties of the terrain lead to different maximum likelihood estimators (MLEs). The Cramer-Rao lower bounds (CRLB) are used to study estimator performance versus emitter velocity for each case. The proposed estimators are successfully demonstrated using field data collected at White Sands Missile Range (WSMR) during the DARPA/Navy Mountaintop program     

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.     

Constrained bandwidth waveforms with minimal dilation sensitivity

Bandpass waveforms which have envelopes which are insensitive to this velocity-induced time dilation can be efficiently processed by narrowband receivers in which envelope correlation is fixed and Doppler tested using fast Fourier transform (FFT) processing. The peak level of the waveform ambiguity function (AF) can be used to gauge the distortion of the waveform induced by dilation. The degree of AF attenuation is shown to be proportional to the dilation parameter or velocity, waveform traveling wave (TW) product, and a sensitivity parameter which depends on the envelope function utilized. Classes of symmetric, constrained bandwidth, phase modulated envelope functions which are minimally dilation sensitive (Doppler tolerant) are derived. When the resulting waveforms are used with a simple correlation receiver structure and the echo data is derived from slowly fluctuating point scattering in white Gaussian noise, the receiver becomes an uncoupled joint estimator of delay and dilation (Doppler). In the case of the bandpass waveforms, only odd symmetry of the phase modulation (PM) yields an uncoupled estimator     

Optimum Realizable Continuous Range Estimation

The ability to detect the presence or absence of a target is no longer the fundamental design criterion when the vehicle to be tracked is cooperative. In spacecraft tracking or navigation systems, for example, emphasis is placed on post-acquisition performance. Therefore, classical radar theory and design techniques are not specifically applicable. On the other hand, there are optimization techniques for extracting the tracking data from noise that are more to the point. In particular, optimum demodulation theory is directed specifically to the problem of continuously extracting data from a nonlinear modulation process. In this paper, the tracking properties of a multitone PM ranging signal are reviewed and are shown to be nearly optimum for cooperative vehicles. An optimum, but nonrealizable, maximum a posteriori (MAP) continuous estimator of range is derived for this signal. The linearized model of this receiver is the optimum nonrealizable Wiener filter for the data. Interpretation of this optimum nonrealizable estimator leads to a receiver design that is both practical and intuitively satisfying. With the aid of post-detection processing in the Wiener-Hopf sense, almost optimum performance is obtained from the resulting receiver, above threshold.     

DOA estimation using one-bit quantized measurements

The effects 1-bit quantization of the input samples has on the direction-of-arrival (DOA) estimation accuracy are considered. The signal model assumes a single stochastic Gaussian point source that is embedded in white Gaussian noise (WGN). The inherent limitations governed by the extreme clipping of the input data are analyzed using the Cramer-Rao bound (CRB) that is derived for a two-sensor array. In addition, several estimators for the I-bit estimation are discussed. Numerical and analytical analyses of the estimation error reveal weak dependency on signal-to-noise ratio (SNR) with singular behavior of the estimation error in certain DOA angles.     

一种卫星导航接收机固定多波束抗干扰方法

自适应波束形成抗干扰性能受先验信息、通道幅相误差等因素影响较大,在工程应用中实现复杂,鲁棒性较差。针对这一问题,提出了一种卫星导航接收机固定多波束抗干扰方法,该方法将信号空间分为多个子空间,通过最优分配策略选取多个子空间分别实现固定波束指向,并相应地在每个波束后配置独立的卫星捕获跟踪通道组,然后依据最高信噪比准则在所有的子空间中优选卫星进行定位解算。该方法无需先验信息辅助,在抑制干扰信号的同时对卫星信号形成接收增益,在存在工程误差的实际条件下可达到与典型自适应波束形成算法相当的抗干扰性能,且具有鲁棒性强、更易工程实现等优点。最后,通过计算机仿真验证了该方法的有效性。     

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     

Design and Performance of an Adaptive Kalman Receiver for Synchronous Data Transmission

A class of multilevel linear-modulation data-transmission systems, over unknown, slowly time-varying, and bandlimited channels is considered. It is shown how sequence estimation in the presence of Gaussian noise and intersymbol interference can be carried out by means of a discrete Kalman estimator. Moreover, the receiver can be provided with data-aided adaptive loops for performing channel identification, carrier recovery, and timing extraction. A computational method is presented to evaluate the average probability of error of the overall system in the presence of inter-symbol interference, additive noise, and phase-and sampling-synchronization errors. The method is based upon nonclassical one-and two-dimensional quadrature rules, which are outlined in the Appendix. As an example, numerical performance results related to a phase-shift-keying (PSK) system are given. The results are obtained by means of general-purpose and system-oriented computers.     

Noncoherent Detection of Split-Phase FSK by Multiple Predetection Filtering

When the cumulative drift in the center frequency of a binary split-phase FSK signal exceeds the peak deviation of the signal, a conventional noncoherent receiver (i.e., one provided with only two IF filters) may be unable to achieve the probability of error per bit which the designer desires. This limitation may be overcome if the receiver is provided with a bank of more than two contiguous filters (each followed by an envelope detector) tospan the total IF band the instantaneous IF signal might occupy. It is shown that the probability of error per bit for such a receiver is a function of 1) the ratio F of peak frequency deviation to peak frequency drift, 2) the number M of IF filter/detectors, and 3) the signal-to-noise ratio ? in the output of the filter containing the signal. It is further shown thatfor a given value of F an increase in M reduces the amount of transmitter power the communication system designer must provide to yield a given probability of error per bit.     

Maximum likelihood azimuth estimation applied to SSR/IFF systems

A conventional (nonmonopulse) secondary surveillance radar (SSR) is significantly cheaper than a monopulse SSR but exhibits much greater azimuthal error, especially when some of the replies are missing. Estimation techniques and their performance are discussed with special reference to SSR applications, and a novel estimator for conventional SSR is described. The proposed technique is a close approximation of the maximum-likelihood estimator (MLE), taking into account the receiver characteristics as well as the missed replies. Estimator performance obtained by analysis and computer simulation is compared with that of conventional estimators that are based on the leading and trailing edges of binary sequences and shows significantly improved accuracy     

ECCM capabilities of an ultrawideband bandlimited random noise imaging radar

Investigated here is high-resolution imaging of targets in noisy or unfriendly radar environments through a simulation analysis of the ultrawideband (UWB) continuous-wave (CW) bandlimited random noise waveform. The linear FM chirp signal was selected as a benchmark radar waveform for comparison purposes. Simulation of the recovery of various types of target reflectivity functions (TRFs) for these waveforms were performed and analyzed. In addition, electronic counter-countermeasure (ECCM) capabilities for both types of systems were investigated. The results are compared using the error between the interference (jamming)-free recovered TRF and the recovered TRF under noisy conditions as a function of the signal-to-interference/jamming ratio (SIR/SJR). Our analysis shows that noise waveforms possess better jamming immunity (of the order of 5-10 dB improvement over the linear FM chirp) due to the unique radar correlation processing in the receiver.     

A novel multistage estimation of signal parameters

A multistage estimation scheme is presented for estimating the parameters of a received carrier signal possibly phase-modulated by unknown data and experiencing very high Doppler, Doppler rate, etc. Such a situation arises, for example, in the case of the Global Positioning Systems (GPS). In the proposed scheme, the first-stage estimator operates as a coarse estimator of the frequency and its derivatives, resulting in higher RMS estimation errors but with a relatively small probability of the frequency estimation error exceeding one-half of the sampling frequency (an event termed cycle slip). The second stage of the estimator operates on the error signal available from the first stage, refining the overall estimates, and in the process also reduces the number of cycle slips. The first-stage algorithm is a modified least-squares algorithm operating on the differential signal model and referred to as differential least squares (DLS). The second-stage algorithm is an extended Kalman filter, which yields the estimate of the phase as well as refining the frequency estimate. A major advantage of the proposed algorithm is a reduction in the threshold for the received carrier power-to-noise power spectral density ratio (CNR) as compared with the threshold achievable by either of the algorithms alone     

Optimum detection and location estimation of target lines in the range-time space of a search radar

The average likelihood ratio detector is derived as the optimum detector for detecting a target line with unknown normal parameters in the range-time data space of a search radar, which is corrupted by Gaussian noise. The receiver operation characteristics of this optimum detector is derived to evaluate its performance improvement in comparison with the Hough detector, which uses the return signal of several successive scans to achieve a non-coherent integration improvement and get a better performance than the conventional detector. This comparison, which is done through analytic derivations and also through simulation results, shows that the average likelihood ratio detector has a better performance for different SNR values. This result is justified by showing the disadvantages of the Hough method, which are eliminated by the optimum detector. To have an estimate for the location of the detected target line in the optimum detection method as the Hough method, which detects and localizes the target lines simultaneously, we present the maximum a posteriori probability estimator. The estimation performance of the two methods is then compared and it is shown that the maximum a posteriori probability estimator localizes the detected target lines with a better performance in comparison with the Hough method.     

On the Performance of Some Sequential Multiple-Decision Procedures

The performance of several sequential procedures for the following multiple-decision problem is investigated. Samples from k random processes (or populations) are available, k at a time (one from each process), to a receiver or data processor. One process contains a signal; the other k - 1 are statistically identical noise. The receiver is to select the odd process (locate the signal), with prescribed probability of error. The optimal receiver makes the selection in minimum average time. Analytical and Monte Carlo computations were performed under the hypothesis that the processes sampled are Rayleigh; however, a method for extrapolating results to other cases is given. The parameter k is allowed to vary from 2 to 1000.     

New Centroid Algorithm Based upon Amplitude-Angle Signature

A method of estimating the centroid location of a target utilizing radar scan return amplitude versus angle information is presented. The method is compared with three thresholding estimators and a first moment estimator in a computer-simulated automatic landing system. This new method is the most robust and accurate during periods of low signal-to-noise ratio. In periods of high signal-to-noise ratio the method has less error than the thresholding methods and is similar in accuracy to the first moment estimator. Furthermore, the number of pulse transmissions required to obtain a desired level of performance in noise is much less than that needed for the thresholding methods and the first moment estimator employed in this simulation.     

Spatial Correlation of Reverberation Noise in Active Sonar

A linear array of hydrophones is considered for detecting a signal echo from a stationary target in the presence of reverberation. The structure of the optimum (likelihood ratio) detector is compared with that of a beamformer-matched filter detector. The conditions causing an increase in the spatial noise correlation between two hydrophones are the conditions under which the optimum spatial detector performs significantly better than the beamforming detector. A study of the space-time correlation function of reverberation shows that 1) a decrease in scatterer angular spread (or a narrowing of the receiver directivity pattern) tends to increase the spatial correlation, 2) if the scatterer Doppler spread is much less than the signal carrier frequency and if the angular spread is uniform, it is still possible to get a high correlation if the intersensor distance is much smaller than the carrier wavelength. These conditions indicate situations where optimum techniques may be worthwhile.