Estimation of the directions of arrival of signals in unknowncorrelated noise. I. The MAP approach and its implementation

The authors propose a method of direction of arrival (DOA) estimation of signals in the presence of noise whose covariance matrix is unknown and arbitrary, other than being positive definite. They examine the projection of the data onto the noise subspace. The conditional probability density function (PDF) of the projected data given the signal parameters and the unknown projected noise covariance matrix is first formed. The a posteriori PDF of the signal parameters alone is then obtained by assigning a noninformative a priori PDF to the unknown noise covariance matrix and integrating out this quantity. A simple criterion for the maximum a posteriori (MAP) estimate of the DOAs of the signals is established. Some properties of this criterion are discussed, and an efficient numerical algorithm for the implementation of this criterion is developed. The advantage of this method is that the noise covariance matrix does not have to be known, nor must it be estimated     

Estimation of the directions of arrival of signals in unknowncorrelated noise. II. Asymptotic behavior and performance of the MAPapproach

For pt.I see ibid., vol.40, no.8, p.2007-17 (1992). The asymptotic behavior and the statistical performance of the maximum a posteriori (MAP) estimate of the directions of arrival (DOAs) of signals applicable in an environment where the sensor noise is unknown and correlated. Computer simulations were performed to confirm the correctness of the performance analysis, and a comparison of the performance of the MAP estimate with other methods is also presented     

Single-antenna blind receiver for multiuser detection in unknowncorrelated noise

The problem of blind multiuser detection for direct-sequence code-division multiple-access systems operating over fading dispersive channels and in the presence of additive Gaussian noise with unknown temporal correlation function is considered. Such a problem has been addressed by Wang and Poor (1999) and solved by employing a receiver with two well-separated antennas, such that the noise is spatially uncorrelated. A new method, which enables blind multiuser detection in correlated noise with just one antenna (and thus can be implemented in mobile transceivers), is proposed here. The effectiveness of the new procedure is tested through computer simulations, and its performance is compared to that of the algorithms developed by Wang and Poor (1999) and Wang and Host-Madsen (1999). Numerical results demonstrate that the newly proposed method, while relying on halved hardware resources, incurs a performance loss of only a few decibels with respect to the two-antenna based procedures     

Decoding of trellis-encoded signals in the presence of intersymbolinterference and noise

A novel receiver for data-transmission systems using trellis-coded modulation is investigated. It comprises a whitened-matched filter and a trellis decoder which combines the previously separated functions of equalization and trellis-coded modulation (TCM) decoding. TCM encoder, transmission channel, and whitened-matched filter are modeled by a single finite-state machine with combined intersymbol interference and code states. Using ISI-state truncation techniques and the set-partitioning principles inherent in TCM, a systematic method is then developed for reducing the state complexity of the corresponding ISI and code trellis. A modified branch metric is used for canceling those ISI terms which are not represented by the trellis states. The approach leads to a family of Viterbi decoders which offer a tradeoff between decoding complexity and performance. An adaptive version of the proposed receiver is discussed, and an efficient structure for reduced-state decoding is given. Simulation results are presented for channels with severe amplitude and phase distortion. It is shown that the proposed receiver achieves a significant gain in noise margin over a conventional receiver which uses separate linear equalization and TCM decoding     

MSK-type signals in the presence of adjacent channel interferenceand white noise

In this letter, the problem of adjacent channel interference (ACI) caused by the close packing of constant envelope MSK-type users in a given frequency band is considered. An optimal receiver filter, based on the theory of matched filtering, is found, and it serves as an upper bound on the signal-to-interference ratio. The intersymbol interference (ISI) caused by the time response of the matched filter is eliminated by a decision feedback equalizer (DFE) which, however, degrades performance. It was found that the matched-filter upper bound allows about 3-15 dB more ACI than the performance of a classical correlation detector (for additive white Gaussian noise only), depending on the frequency separation between channels. The DFE performance is only a little bit worse than that of the matched filter     

Estimation of the number of orthogonal signals with unknown parameters

Algorithms for estimation of the number of signals with unknown amplitudes and several non-energy parameters are synthesized on the basis of the modified maximum likelihood method. Asymptotic values of the probabilities of the error in estimation of the signal number are determined. The effect of a reduced volume of the a priori domain of possible values and the dimensionality of the vector of unknown non-energy parameters on the quality of operation of the algorithms for estimation of the number of signals is investigated.     

Estimation of multilevel digital signals in the presence ofarbitrary impulsive interference

We first study the a posteriori probability density function of the state of a discrete-time system given the measurement data. By applying the Bayesian law to the state and measurement equations of the stochastic system, the a posteriori density is obtained in closed-form and computed recursively for arbitrary i.i.d. state noise and any discrete-type measurement noise (or multilevel digital signal). Then, our effort concentrates on the estimation of impulsive noise which interferes the multilevel signal of interest. By considering the L^p -metric performance criterion, where 0相似文献   

高斯色噪声下的相干信号 DOA 高分辨率估计*

针对高斯有色噪声下的DOA估计问题,提出一种基于高阶累积量稀疏表示的DOA估计方法。该方法利用四阶累积量矩阵中的第一列生成最小冗余向量,利用扩展阵列的最小冗余导向矢量构造过完备字典。然后利用L1范数作为稀疏约束条件,建立最小冗余向量的稀疏模型进行DOA估计。该方法将求解四阶累积量的次数从M4次降为M2-M+1次。同时又能充分利用四阶累积量的优点,对高斯有色噪声具有良好的抑制能力,并使阵列孔径得到了扩展,估计信号个数能大于阵元数目。仿真实验和理论分析验证了该方法比MUSIC-like和MUSIC算法具有更好的性能,不需要任何处理可以直接应用到相干信号。     

Adaptive energy detection of quasi-deterministic signals in the presence of the non-Gaussian noise

Analytical expressions for the parameters of the adaptive energy detection of the quasi-deterministic radio signals in the presence of the Lichter noise are derived. The effect of the random amplitude distribution of radio signals on the decision statistics of detection is analyzed.     

Estimation and detection of signals in multiplicative noise (Corresp.)

We consider a class of matrix signal processes that are received in the presence of multiplicative observation noise. By examining the differential version of the observation, we are able to derive finite-dimensional optimal detection-estimation equations that involve a linear filter with gain computed on-line using the incoming observations. An example involving the detection of an actuator failure on a rotating rigid body is considered.     

Exploiting sensor redundancy for the calculation of fractional derivatives in the presence of noise

In this paper a new method for the calculation of the fractional expressions in the presence of sensor redundancy and noise, is presented. An algorithm, taking advantage of the signal characteristics and the sensor redundancy, is tuned and optimized through genetic algorithms. The results demonstrate the good performance for different types of expressions and distinct levels of noise.     

Performance of signals coded by miller code in the presence of noise and interference

In the letter the bit error probability for signals which are coded by the Miller code in the presence of Gaussian noise and interference is determined. The optimal area of the filter bandwidth, the best in accordance with the error probability, is determined.     

Estimation of randomly occurring stochastic signals in Gaussian noise (Corresp.)

This note applies the general likelihood ratio for the minimum-mean-square-error estimation of the signal when the presence of the signal at the receiver is uncertain during the entire observation interval.     

Asymptotic performance analysis of information-theoretic criteriafor determining the number of signals in spatially correlated noise

A new information-theoretic criterion for the determination of the number of signals in unknown correlated noise was derived in Zhang and Wong (1993) supported with computer simulations. In the present correspondence, the theoretic performance of the criterion is presented. The authors establish a simple expression, in a closed form, for the probability of correct estimation by the criterion. Then on this basis, they analyze its consistency properties, showing that the criterion is consistent if the penalty coefficient α=(1/2)logN and inconsistent if α=1     

Bit-error probability for optimum combining of binary signals in the presence of interference and noise

We derive an exact bit-error probability (BEP) expression for coherent detection of binary signals with optimum combining in wireless systems in the presence of multiple cochannel interferers and thermal noise. A flat Rayleigh fading environment with space diversity, uncorrelated equal-power interferers, and additive white Gaussian noise is considered. The approach is to use the chain rule of conditional expectation together with the joint probability density function (pdf) of the eigenvalues of the interference correlation matrix. This joint pdf is related to the Vandermonde determinant. Let N/sub A/ denote the number of antennas and N/sub I/ the number of interferers. We consider both the cases of an overloaded system, in which N/sub I//spl ges/N/sub A/, and an underloaded system, in which N/sub I/相似文献   

Linear prediction analysis of speech signals in the presence ofwhite Gaussian noise with unknown variance

A simple method is presented to compensate for noise effects before performing linear prediction analysis of speech signals in the presence of white noise with unknown variance. The method determines a suitable bias that should be subtracted from the zero-lag autocorrelation function, rather than deriving the exact noise variance. The resulting linear prediction filter is guaranteed to be stable. Since the bias used is always smaller than the minimum eigenvalue of the autocorrelation matrix. In addition to a comparison with other methods, the proposed method is examined from various viewpoints, including the degree of formant intensity, signal-to-noise ratio (SNR), deviation of compensated spectra and objective distortion measures. The improvements observed across a data set, consisting of four sentences uttered by six speakers, indicate that the compensated spectra measured with low SNRs are comparable to the uncompensated counterparts measured with approximately 5 dB higher SNRs     

Estimation of the number of operating sensors in large-scale sensor networks with mobile access

This paper investigates the estimation of the number of operating sensors in a sensor network in which the data collection is made by a mobile access point. In this paper, an estimator based on the Good-Turing estimator of the missing mass is proposed and it is generalized to other related problems such as the estimation of the distribution of energy available at sensors. The estimator is analyzed using the theory of large deviations. Closed-form bounds on the large deviation exponent are presented and confidence intervals for the estimator are characterized.     

Optimal coherent detection of FSK signals with imbalance amplitudes in the presence of colored gaussian noise

The problem of optimal coherent detection of frequency-shift keying (FSK) signals transmitted over an additive colored Gaussian noise channel with imbalance gains in different frequencies (IGDF-ACGN channel) is studied. The structure of the optimal coherent detector is derived. Theoretical analysis and computer simulation results show that the detector is optimal in either additive colored Gaussian noise environment or additive white Gaussian noise environment.     

Estimation of the number of signals from features of the covariancematrix: a supervised approach

The purpose of this paper is to provide a fast and simplified detection test for use in the presence of a small number of sources (from 0-2), which is able to accommodate correlated paths and nonwhite noise; conventional eigenvalue-based criteria are unable to do so. For a uniform linear array, using common sense arguments, a small set of significant features of the covariance matrix are used as inputs to a neural net. The nonlinear transfer function of the neural net is adjusted by supervised training to provide the discriminant functions for order selection in its outputs. Results from the net are then compared with conventional criteria and demonstrate superior performance, in particular, for correlated sources and small sample sizes. Training may be introduced for known nonwhite noise, which serves to maintain high performance for reasonable correlation lengths     

Estimation of the relative delay of two similar signals of unknown phases in white Gaussian noise

In this paper we consider the estimation of the delay of a signal of unknown phase obscured by white noise and by another signal of unknown phase and known delay. We also consider the situation where both delays are unknown. Use is made of Shannon's sampling analysis^{1}as developed by Woodward.^{2}We conclude that the relative carrier phase of the two signals must be first estimated in order to maximize the {em a posteriori} probability of the estimate, but that knowledge of the absolute phase is only of secondary value.