Joint Estimation Of Time Delay Research Articles

Fast Tensor-Based Joint Estimation for Time Delay and Angle of Arrival in OFDM System

Nowadays, the joint estimation of time delay (TD) and angle of arrival (AOA) using conventional vector structure suffers from the considerable complexity of multidimensional spectrum search. Therefore, a fast estimation method using orthogonal frequency division multiplexing (OFDM) technology and uniform planar array (UPA) is proposed in this paper, which adopts low-complexity tensor-based operations and spatial-frequency features to reconfigure the channel frequency response. To begin with, the array response is integrated with the OFDM signal characteristics to build an extended array in tensor form. Afterwards, we process the covariance matrix of the tensor structure by CANDECOMP/PARAFAC decomposition (CPD) to separate the respective signal subspaces of TD and AOA estimates. Finally, we conduct a one-dimensional (1-D) spectrum search to locate the TD estimates and a two-dimensional (2-D) spectrum search to locate the AOA estimates. The simulated performance demonstrates that the proposed algorithm offers precise estimates at low signal-to-noise ratios in a multipath environment and outperforms traditional vector-based algorithms with respect to computational complexity.

Hyperbolic tangent cyclic correlation and its application to the joint estimation of time delay and doppler shift

Gaussian distribution is a classic model for additive background noise in scientific research. By assuming and applying Gaussian noise, scholars in different fields can apply themselves to fundamental research and propose many innovative theories based upon Gaussianity. As the scope of engineering applications continues to expand, a single model of background noise cannot meet the more stringent conditions, and the errors caused by inappropriate noise models cannot be ignored. In this paper, alpha-stable distribution is utilized to model additive background noise because of the generality of this distribution. Correspondingly, a novel similarity measurement named hyperbolic tangent correlation (HTC) is proposed to replace the conventional correlation. Then, hyperbolic tangent cyclic correlation (HTCC) used in cyclostationary signal processing is proposed and thoroughly studied. HTC and HTCC emphasize preserving the signal of interest (SOI) rather than suppressing the noise, as traditionally practiced. In particular, they effectively process both the amplitude and phase information in the SOI. To demonstrate the superiority of HTCC in processing amplitude and phase information against background noise, a representative application in time-frequency analysis is presented, and the resulting performance is compared to that of the existing methods. Considering the beneficial mathematical properties of the hyperbolic tangent function, we hope that HTC and HTCC will have more applications in signal processing.

Joint Estimation of Time Delay, Doppler Velocity and Doppler Rate of Unknown Wideband Signals

In this work, we consider the joint estimation of time delay, Doppler velocity and Doppler rate of unknown wideband signals, in the sense that the time delay migration over time and Doppler shift migration over signal frequency are non-ignorable. By partitioning the received signals into short-time segments, a novel wideband signal model is presented and the maximum likelihood (ML) estimator is derived. With better compensation of parameter migrations, higher estimation accuracy might be achieved through the derived ML estimator. The signal-specific Cramer–Rao lower bound analysis for the wideband cases is also presented. To avoid the multidimensional search of the ML estimator, a fast estimation algorithm based on the time-reverse transform and the second-order Keystone transform is proposed. In this fast estimation algorithm, these parameters could be estimated through successive one-dimensional searches. Simulation results show that the fast estimation algorithm could achieve comparable performance with the ML estimator with a much lower computational complexity.

Joint Estimation of Time Delay and Doppler Shift for Band-Limited Signals

The standard approach for joint estimation of time delay and Doppler shift of a signal is to estimate the point at which the cross ambiguity function of the original and modified signals attains its maximum modulus. Since band-limited signals can be expressed exactly by their Shannon series, we here consider approximated signals gained by truncating their Shannon series to involve only the sampled signal values. We then estimate the time delay and Doppler shift by calculating a point at which the cross ambiguity function of the approximated signals attains its maximum modulus. This cross ambiguity function has an analytic expression which allows its evaluation at any point, and we may apply Newton's method to calculate accurately and efficiently a point where the maximum modulus is attained. In the numerical experiments we conducted, our method generally outperformed other methods for estimation of both time delay and Doppler shift.

Joint estimation of time delay and frequency delay in impulsive noise using fractional lower order statistics

New methods for time delay estimation and joint estimation of time delay and frequency delay in the presence of impulsive noise are introduced. First, degradation of the conventional approaches based on second-order statistics is shown both theoretically and experimentally. Then, a new class of robust algorithms are developed using the theory of alpha-stable distributions, including the fractional lower order covariance (FLOC) method, which is formulated for the time delay estimation problem and the fractional lower order ambiguity function (FLOAF), which is defined for the joint estimation of time delay and frequency delay. It is shown that these new methods are robust for both Gaussian and non-Gaussian impulsive noise environments. The improved performance is clearly demonstrated through detailed analysis and comprehensive simulations with computer-generated data as well as actual radar and sonar clutter data.

Design of optimum signals for the simultaneous estimation of time delay and Doppler shift

The problem of joint estimation of time delay and Doppler shift is considered from the point of view of the Wigner distribution of the signal. A very efficient method of obtaining the optimum signal with minimum estimation error based on the convexity of the design region is developed. Practical applications, however, require the signal to satisfy other constraints which present complications in acquiring the optimum signal. A design approach based on the method of simulated annealing is suggested to solve for the optimum signal under constraints. The performance of the signals so obtained is evaluated and compared with that of signals obtained by synthesis.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>