Estimation For Wideband Sources Research Articles

Gradient‐projection based super‐resolution wideband DOA estimation using non‐uniform linear arrays

AbstractA new method is developed for the Direction of Arrival (DOA) estimation of wideband sources by refining the initial estimates and posing the super‐resolution theory in a non‐convex optimization problem. A gradient‐projection method is conducted for the accurate estimation of DOAs. The proposed method can be performed by any non‐uniform linear array with no need for any focusing matrices. Moreover, a greedy search algorithm is employed to obtain initial estimates for super‐resolution implementation. Numerical simulations show the outstanding accuracy of the proposed method and more robustness to noise compared to some well‐known methods. It is also more effective for DOA estimation of adjacent sources.

DOA estimation of wideband sources by sparse recovery based on uniform circle array

The conventional direction of arrival (DOA) estimation by compressed sensing is based on wideband focusing and sparse recovery in discrete domain. The former needs high signal to noise ratio (SNR), and the latter requires the space division, or their performance will degrade seriously. Therefore, a new algorithm of wideband DOA calculation in frequency domain based on uniform circle array (UCA) is proposed, the optimisation problems are respectively disposed at each frequency, then the sparse support set is acquired by the corresponding semidefinite programming, after that DOA is calculated through fusing the data of every frequency, simultaneously the original sources can also be reconstructed. This algorithm averts the grid partition in discrete domain, and it also performs well in condition of small samples and low SNR.

DOA estimation of wideband sources by sparse recovery based on uniform circle array

DOA estimation of wideband sources by sparse recovery based on uniform circle array

Wideband DOA estimation based on incoherent signal subspace method

PurposeDirection-of-arrival (DOA) estimation for wideband sources has attracted a growing interest in the recent decade because wideband sources are incorporated in many real-world applications such as communication systems, radar, sonar and acoustics. One way to estimate the DOAs of wideband signals is to decompose it into narrowband signals using discrete Fourier transform (DFT) and then apply well-established narrowband algorithms to each signal. Afterwards, results are averaged to yield the final DOAs. These techniques require scanning the full band of wideband sources, ultimately degrading the resolution and increasing complexity. This paper aims to propose a new DOA estimation methodology to solve these problems.Design/methodology/approachThe new DOA estimation methodology is based on incoherent signal subspace method (ISSM). The proposed approach presents a criterion to select a single sub-band of the selected narrowband signals instead of scanning the whole signal spectrum. Then, the DOAs of wideband signals are estimated using the selected sub-band. Therefore, it is named as single sub-band (SSB)-ISSM.FindingsThe computational complexity of the proposed method is much lower than that of traditional DFT-based methods. The effectiveness and advantages of the proposed methodology are theoretically investigated, and computational complexity is also addressed.Originality/valueTo verify the theoretical analysis, computer simulations are implemented, and comparisons with other algorithms are made. The simulation results show that the proposed method achieves better performance and accurately estimates the DOAs of wideband sources.

Direction-of-arrival and Range Estimation of Wideband Sources in the Near Field

In this letter, we address the problem of wideband sources localization in the near field of the sensor array. It is shown that the spatial sampling rate can be considered as a function of temporal frequency so that wideband sources can be represented in the spatial frequency domain. A computationally efficient localization method is then developed based on the Toeplitz matrices constructed from the frequency-dependent cross-correlation between sensors. This allows us to resolve near field sources with quite a few numbers of sensors. Indeed, the sources can be located with fewer sensors. Finally, the simulation results are presented to validate the performance of the proposed method.

Three dimensional parameters estimation of wideband sources based on matching pursuit

This paper proposes an algorithm for estimating three dimensional parameters of wideband sources using L array, which is based on Matching Pursuit against the deficiencies of traditional direction finding algorithms and sub-space algorithms. The new approach presented in this paper first constructs atom-dictionaries according to system models and then projects observations of L array onto dictionaries, and finally estimates initial frequency, FM slope, elevation and azimuth angles of chirp sources by solving least squares problems when applied into wideband cases. The simulation results show the method has good performance in low signal-to-noise ratio, and the chirps are well localized, which proved the effectiveness of the proposed algorithm.

A Modified Wideband Direction of Arrival Estimator Based on Spectrum Smoothin

DOA estimation for wideband sources with sensor arrays is one of the key issues in acoustic tracking. An improvement on the wideband DOA estimation is proposed. The new covariance matrix of the frequency bin is obtained by averaging the covariance matrices of its adjacent frequency bins, and then the general wideband algorithms are used to estimate the DOAs. Compared with the wideband algorithm without covariance matrix smoothing, the improvement has higher resolution and smaller root mean square error except high signal-noise-ratio. The theoretical expressions indicate that the improvement is effective. The performance of the improvement is also demonstrated and analyzed through the computer simulations.

FRFT Based Method to Estimate DOA for Wideband Signal

This paper presents a new direction-of-arrival (DOA) estimation for wideband sources, using fractional Fourier transform with fitting angle (F3A). Unlike other coherent wideband methods, the new method does not require any preprocessing for initial values and decomposing into narrowband components. This new technique estimates DOA by rotating the time frequency plate with the fitting angle to fit the time frequency distribution approximately. The algorithm can be applied to arbitrary shaped one dimensional or two dimensional arrays. The signal frequency can be higher than the frequencies in many wideband algorithms. The performance of this wideband technique is compared with that of the new method through simulations. The simulations show that this new technique performs better than others, while this algorithm does not apparently vary with signal-to-noise ratio (SNR).

DOA estimation of wideband sources without estimating the number of sources

In this paper, we propose a new technique to estimate wideband source directions from the sensor snapshots without requiring to know the number of sources present in the scenario. This work is motivated by the fact that the existing model order estimation (number of sources) techniques for wideband source scenario are either inaccurate or computationally expensive. Direction-of-arrival (DOA) estimation is realized using a beamformer framework which imposes nulls in the spatial spectrum along the source directions. The null width along the frequency axis is widened by introducing a new data dependent term into the optimization problem, thus achieving wideband capability. Furthermore, the temporal processing of the data snapshots drastically reduces the number of snapshots required for wideband DOA estimation. The effectiveness of the proposed formulation is studied with simulated experiments.

2-D spatial-spectrum estimation for wide-band sources based on interpolated circular arrays

In array signal processing, 2-D spatial-spectrum estimation is required to determine DOA of multiple signals. The circular array of sensors is found to possess several nice properties for DOA estimation of wide-band sources. C. U. Padmini, et al. (1994) had suggested that the frequency-direction ambiguity in azimuth estimation of wide-band signals received by a uniform linear array (ULA) can be avoided by using a circular array, even without the use of any delay elements. In 2-D spatial-spectrum estimation for wide-band signals, the authors find that it is impossible to avoid the ambiguity in source frequency-elevation angle pairs using a circular array. In this paper, interpolated circular arrays are used to perform 2-D spatial-spectrum estimation for wide-band sources. In the estimation, a large aperture circular array (r > λmin/2) is found to possess superior resolution capability and robustness.

Simultaneous spatial separation and direction-of-arrival estimation of wideband sources using bootstrapped algorithms

This paper presents two versions of a novel adaptive algorithm for simultaneous spatial separation and direction finding of two wideband, uncorrelated sources received by two separated sensors. The algorithm provides estimates of the spatial location of the sources (direction of arrival-DOA) and outputs two signals which are filtered versions of the source signals. We describe the different configurations of the separation system and study sensitivity of the two signal estimates to the accuracy in estimating the DOA of the sources. We show that perfect separation is achieved even if the DOAs are not perfectly estimated, at the cost of degradation in the output signal-to-noise-ratio. Then we propose implementation of an adaptive control algorithm and we discuss the steady state performance in the presence of an additive noise. We compare the complexity, performance and noise immunity of the two versions of the proposed algorithm.

078 Maximum likelihood location estimation of wideband sources using the EM algorithm

078 Maximum likelihood location estimation of wideband sources using the EM algorithm