Remarks, mostly historical, on signal detection and signal parameter estimation

Historical remarks outlining some of the evolution of the statistical theory of detecting signals in noise and of estimating signal parameters make up the greater part of the paper. The time period covered is roughly from the years of World War II to the middle 1960s. The remarks are rather severely limited in scope; they do not touch on nonparametric statistical methods, or filtering, or prediction theory, for example. The last part of the paper is a discussion of one aspect of a signal-processing problem area that is of current interest in optics and radar, and can be regarded as one of many descendants of the early parameter estimation theory. The area is object-field reconstruction or restoration, and the aspect of interest is the intrinsic relation between the inherent instability of solutions of many such problems and the precision or resolution of detail that can be attained in the construction.     

Joint symbol detection and channel parameter estimation inasynchronous DS-CDMA systems

A method for jointly estimating the time delay and complex gain parameters, as well as detecting the transmitted symbols in an asynchronous multipath DS-CDMA system, is presented. A short training sequence is used to obtain a coarse estimate of the channel parameters, which is consequently used to detect the symbols. By exploiting structure in the digitally modulated signals, the method iterates to (i) improve the estimate of the channel parameters and (ii) reduce the probability of incorrect detection. The method's efficacy is demonstrated by numerical simulations     

Multicarrier signal detection and parameter estimation infrequency-selective Rayleigh fading channels

A new joint signal detection and channel parameter estimation scheme is proposed for multiple subcarrier signaling with pilot symbol-assisted modulation (PSAM) schemes. The proposed scheme estimates a pair of parameters associated with the generation process of the fading frequency selectivity, which is common to all the subcarriers. This parameter estimation can effectively extract information regarding the fading frequency selectivity through the pilot symbols received not only by the subcarrier of interest, but by other ones as well. The fading complex envelope with each subcarrier is derived from the estimates of the parameter pair. With the proposed scheme, performances are evaluated through simulations and are compared with the performance of a subcarrier-by-subcarrier detection scheme     

Joint parameter estimation and symbol detection for linear ornonlinear unknown channels

We present an iterative method for joint channel parameter estimation and symbol selection via the Baum-Welch algorithm, or equivalently the Expectation-Maximization (EM) algorithm. Channel parameters, including noise variance, are estimated using a maximum likelihood criterion. The Markovian properties of the channel state sequence enable us to calculate the required likelihood using a forward-backward algorithm. The calculated likelihood functions can easily give optimum decisions on information symbols which minimize the symbol error probability. The proposed receiver can be used for both linear and nonlinear channels. It improves the system throughput by making saving in the transmission of known symbols, usually employed for channel identification. Simulation results which show fast convergence are presented     

Joint parameter/state estimation

It is shown how the refined instrumental variable method of parameter/state estimation for single-input single-output (s.i.s.o.) systems proposed by Young1 can be extended to multi-input multi-output (m.i.m.o.) systems. As might be expected, the extension follows directly from the s.i.s.o. analysis, but involves some difficult and interesting matrix manipulations.     

低信噪比条件下DS信号的检测和参数估计

本文在对目前存在的各种DS信号检测方法进行充分分析、研究的基础上，提出了一种预处理修正周期的DS检测方法。计算机模拟表明，与其他方法相比，该算法具有较好的检测和参数估计性能。     

Joint transmitter-receiver optimization in synchronous multiusercommunications over multipath channels

Transmitter optimization, in addition to receiver optimization, contributes significantly to efficient interference suppression in multiple access and multipath channels. The system design is based on the joint optimization of the transmitter and the receiver in a synchronous multiuser channel characterized by multipath propagation. Joint optimization is represented by a linear transformation of the transmitted signals at the transmitter and a linear transformation of received signals at each receiving site that minimize the effect of multiple access and multipath interference. The minimum mean squared error between the true bit value and its estimate at the output of the receiver is taken as the cost function, subject to average and peak transmit power constraints. It is shown that joint transmitter-receiver optimization outperforms significantly either transmitter optimization or receiver-based techniques. The crucial assumption, in the case of multipath channels, is that the transmitter knows the multipath characteristics of all channels and that the channel dynamics are sufficiently slow so that multipath profiles remain essentially constant over a block of preceded bits. The practical applications can be found in indoor and cellular communications, satellite communications, or military communications where nonorthogonal signature waveforms are employed     

Joint space-time parameter estimation for wireless communicationchannels

Joint space-time parameter estimation methods are discussed for time-varying channels in a multipath environment. A spatiotemporal array manifold model is developed that makes it possible to apply traditional parameter estimation techniques for extracting both the angle and delay parameters from the observed data. The conditional Cramer-Rao bound (CRB) is derived for unbiased space-time parameter estimators     

Some lower bounds on signal parameter estimation

New bounds are presented for the maximum accuracy with which parameters of signals imbedded in white noise can be estimated. The bounds are derived by comparing the estimation problem with related optimal detection problems. They are, with few exceptions, independent of the bias and include explicitly the dependence on the a priori interval. The new results are compared with previously known results.     

Joint maximum-likelihood parameter estimation for burst DSspread-spectrum transmission

We first derive the joint optimal maximum-likelihood (ML) estimator of the carrier phase, both Doppler shift and Doppler rate, and the spreading code delay for a short burst direct sequence/spread spectrum (DS/SS) transmission in the absence of the data modulation. The typical burst duration is three data bit periods (60 ms). The performance of the joint estimator is analytically derived separately for high and low carrier-to-noise ratio (CNR) values. A suboptimal ML estimator based on the method of averaged periodogram is proposed for the data modulation present case, allowing the joint estimation of the data bit values. Then the above parameters are assumed correctly estimated and a segmentation approach is adopted, deriving the optimal joint ML estimator for the bit synchronization epoch and data. Simulations show the joint estimators perform reliable down to a CNR of approximately 30 dB·Hz     

Robust parameter estimation of a deterministic signal in impulsivenoise

This paper presents a robust class of estimators for the parameters of a deterministic signal in impulsive noise. The proposed technique has the structure of the maximum likelihood estimator (MLE) but has an extra degree of freedom: the choice of a nonlinear function (which is different from the score function suggested by the MLE) that can be adjusted to improve robustness. The effect of this nonlinear function is studied analytically via an asymptotic performance analysis. We investigate the covariance of the estimates and the loss of efficiency induced by nonoptimal choices of the nonlinear function, giving special attention to the case of α-stable noise. Finally, we apply the theoretical results to the problem of estimating the parameters of a sinusoidal signal in impulsive noise     

一种LFM信号最大似然估计模型与参数估计快速算法

从最大似然估计模型入手,提出了一种适合在一般高斯噪声环境（包括色噪声）下LFM信号目标的参数估计模型和基于此估计模型的调频斜率和初始频率估计的快速算法。此方法获得了最大似然方法估计精度高的优点,且运算量比传统的最大似然方法大大降低。另外推导出了一般高斯环境下的LFM参数估计的CRB界,为一般高斯环境下的估计的参数的方差提供实际下界。     

A subspace rotation approach to signal parameter estimation

A new approach to Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) is described in the context of direction-of-arrival estimation, but is also applicable to other problems. The method relies on finding the underlying rotation between the common subspaces associated with an array of pairwise-matched and codirectional sensor doublets. ESPRIT has several remarkable advantages over earlier techniques such as MUSIC, and also provides asymptotically unbiased and efficient estimates.     

Joint iterative interference cancellation and parameter estimation for cdma systems

This letter proposes a unified approach to joint iterative parameter estimation and interference cancellation (IC) for uplink CDMA systems in multipath channels. A unified framework is presented in which the IC problem is formulated as an optimization problem of an IC parameter vector for each stage and user. We also propose detectors based on a least-squares (LS) joint optimization method for estimating the linear receiver filter front-end, the IC, and the channel parameters. Simulations for the uplink of a synchronous DS-CDMA system show that the proposed methods significantly outperform the best known IC schemes.     

Joint channel estimation and data detection in space-time communications

The paper considers joint channel estimation and data sequence detection for multipath radio channels with multiple antennas at the transmitter and/or receiver. An iterative space-time receiver based on the expectation-maximization algorithm is proposed. We examine the performance of this receiver for transmit diversity and space-time coding methods over Rayleigh fading channels. Simulation results show that the receiver can often achieve near-coherent performance with modest complexity and using very few pilot symbols.     

Detection and parameter estimation of a transient signal usingorder statistics

Detection and parameter estimation of a transient signal in noise is a problem of many applications. It is characterized by the fact that some of the measurements consist of noise only. Modern statistical signal processing techniques are applied on a discrete version of the received data and are implemented by digital signal processing (DSP). In this correspondence, we show how order statistics (OS)-based signal processing, which is of a discrete nature, can be used for simultaneous detection and estimation of parameters (such as time of arrival and signal duration) of a sampled transient signal in white noise. We show that the resulting processors are more robust than the conventional processors, whereas their performance is about the same, at the cost of increased computational complexity     

Some results on the stochastic signal parameter estimation problem

The problem of finding maximum-likelihood estimates of the partially or completely unknown autocorrelation function of a zero-mean Gaussian stochastic signal corrupted by additive, white Gaussian noise is analyzed. It is shown that these estimates can be found by maximizing the output of a Wiener estimator-correlator receiver biased by a smoothed version of the output noise-to-signal ratio of the Wiener estimator over the class of admissible autocorrelation functions. For the case where the autocorrelation function is known except for an amplitude scale parameter, an illuminating expression for the Cramer-Rao minimum estimation variance is derived. Detailed study of this expression yields, among other results, an interpretation of the maximum-likelihood estimator as an adaptive processor.     

一种扫频干扰信号参数估计方法

现代的干扰信号越来越多的采用复杂的信号波形和调制样式,为了解决对干扰信号时频分析中出现的时间分辨率和频率分辨率无法兼顾的问题,得到更加清晰明确的时频关系图,本文提出了基于平滑伪 Wigner-Ville分布（SPWVD）的时频分析方法,并通过对干扰信号的分析处理结果验证了该方法的有效性。