Direction Of Arrival Estimation Of Signals Research Articles

DOA Estimation of Noncircular Signals for Unfolded Coprime Linear Array: Identifiability, DOF and Algorithm (May 2018)

An ambiguity-free direction of arrival (DOA) estimation method is presented for unfolded coprime linear array (UCLA) in this paper to resolve noncircular signals. Unlike the existing methods which process the two subarrays of coprime linear array separately, we stack the received signals of the two subarrays and derive the total subspace to produce the MUSIC spectrum. Specifically, we demonstrate that the ambiguity problem can be suppressed owing to the coprime property and the true DOA estimates can be obtained immediately. As the self-information and mutual information are jointly employed, the proposed method can achieve the full degrees of freedom (DOFs) and improved DOA estimation performance. Meanwhile, the extended aperture of UCLA can be feasibly exploited, which endows the proposed method with an enhanced identifiability. In addition, the non-circularity is utilized to double the available DOF and further improve the estimation accuracy of the proposed method. Simulation results verify the effectiveness and superiority of the proposed method.

Sparse representation-based DOA estimation of coherent wideband LFM signals in FRFT domain

In this paper, the method of direction-of-arrival (DOA) estimation for wideband signals based on sparse representation of FRFT domain is proposed by using the excellent convergence of FRFT to LFM signals. This method focuses the wideband signal to the reference frequency using FRFT, establishes the DOA estimation model and the array manifold matrix in the FRFT domain, and reconstructs the spatial spectral function based on the sparse representation of the spatial angles, so as to realize the wideband LFM signal DOA estimations. The method not only is suitable for non-coherent signals but also can process coherent signals directly without any decoherent operations; in addition, the number of signals is not necessarily known a priori. Simulation results show that the proposed method can achieve better estimation performance and higher angular resolution, especially under low signal-to-noise ratio (SNR) condition.

Broadband VHF Localization of Lightning Radiation Sources by EMTR

In this paper, a novel mapping algorithm by applying electromagnetic time reversal (EMTR) technique to broadband very high frequency (VHF) for the direction-of-arrival (DOA) estimation of lightning radiation sources is proposed and validated. Based on the theory of array signal DOA estimation and time reversal (TR) principle, the lightning radiation receiving model with broadband VHF array is established, and thereafter the TR synthesized signal for arbitrary direction is derived. It is proved that the direction with the maximum norm of synthesized signal is the optimal estimation for the incident direction, and hence the procedure for the EMTR-VHF method is derived. Numerical simulations are conducted for testing the algorithm and investigating the relationships between the array spatial resolution and the available signal frequencies, robustness of the algorithm, et al . Two metrics, amplitude ratio and energy ratio, are devised to filter false locations, and the acceptable ranges of them are further estimated by simulation. In order to further validate the EMTR-VHF algorithm, field experiments are carried out. The results show that the EMTR-VHF method performs well, especially for the sources with low elevations, with the error less than 1°. Finally, the application of EMTR-VHF method in locating a negative cloud-to-ground flash is presented. Temporal and spatial development of the leader-return stroke sequence could be well depicted. The results are generally consistent with the VHF interferometry technique, which confirm its ability in lightning localization. Besides, the discrepancy between this algorithm and broadband interferometry method are documented.

DOA Estimation of Noncircular Signals with Combined ESPRIT for Coprime Linear Array

Direction of arrival (DOA) estimation of noncircular signals for coprime linear array is investigated, and a combined estimation of signal parameters via rotational invariance technique (ESPRIT) based algorithm is proposed. The coprime linear array can be de-composed into two uniform linear arrays, so ESPRIT is firstly used to obtain ambiguous DOA estimations, then unique DOA estimation is achieved by finding the coincide results from the two decomposed subarrays based on the coprimeness. The proposed algorithm increase the degree of freedom, enhance the performance of angle estimation, and identifies more targets than conventional methods. Numerical simulations are conducted to demonstrate the improvement of the proposed algorithm.

Sparsity-aware DOA estimation of quasi-stationary signals using nested arrays

Direction of arrival (DOA) estimation of quasi-stationary signals (QSS) impinging on a nested array in the context of sparse representation is addressed in this paper. By exploiting the quasi-stationarity and extended virtual array structure provided inherently in the nested array, a new narrowband signal model can be obtained, achieving more degrees of freedom (DOFs) than the existing solutions. A sparsity-based recovery algorithm is proposed to fully utilise these DOFs. The suggested method is based on the sparse reconstruction for multiple measurement vector (MMV) which results from the signal subspace of the new signal model. Specifically, the notable advantages of the developed approach can be attributed to the following aspects. First, through a linear transformation, the redundant components in the signal subspace can be eliminated effectively and a covariance matrix with a reduced dimension is constructed, which saves the computational load in sparse signal reconstruction. Second, to further enhance the sparsity and fit the sampled and the actual signal subspace better, we formulate a sparse reconstruction problem that includes a reweighted ℓ1-norm minimisation subject to a weighted error-constrained Frobenius norm. Meanwhile, an explicit upper bound for error-suppression is provided for robust signal recovery. Additionally, the proposed sparsity-aware DOA estimation technique is extended to the wideband signal scenario by performing a group sparse recovery across multiple frequency bins. Last, upper bounds of the resolvable signals are derived for multiple array geometries. Extensive simulation results demonstrate the validity and efficiency of the proposed method in terms of DOA estimation accuracy and resolution over the existing techniques.

DOA estimation of noncircular signals for coprime linear array via locally reduced-dimensional Capon

ABSTRACTWe investigate the issue of direction of arrival (DOA) estimation of noncircular signals for coprime linear array (CLA). The noncircular property enhances the degree of freedom and improves angle estimation performance, but it leads to a more complex angle ambiguity problem. To eliminate ambiguity, we theoretically prove that the actual DOAs of noncircular signals can be uniquely estimated by finding the coincide results from the two decomposed subarrays based on the coprimeness. We propose a locally reduced-dimensional (RD) Capon algorithm for DOA estimation of noncircular signals for CLA. The RD processing is used in the proposed algorithm to avoid two dimensional (2D) spectral peak search, and coprimeness is employed to avoid the global spectral peak search. The proposed algorithm requires one-dimensional locally spectral peak search, and it has very low computational complexity. Furthermore, the proposed algorithm needs no prior knowledge of the number of sources. We also derive the Crámer-Rao bound of DOA estimation of noncircular signals in CLA. Numerical simulation results demonstrate the effectiveness and superiority of the algorithm.

Direction-of-arrival estimation of multipath signals using independent component analysis and compressive sensing

Multipath signal is often considered an interference that must be removed. The coherence between multipath and direct component makes it difficult to use conventional direction-of-arrival (DOA) estimation methods in a smart antenna system. This study demonstrates a new multipath signal DOA estimation technique. Unlike the common methods, without decoherence preprocessing, the proposed algorithm first apply a complex fast independent component analysis (cFastICA) algorithm to obtain the steering vectors with multipath information that corresponds to each source signal. Then, according to the special structure of the obtained steering vectors and spatial sparsity of the multipath signal components, the algorithm uses the solution of the sparse signal reconstruction problem in the compressive sensing (CS) theory, and the DOA estimation of the multipath signal is translated into an l1 norm minimization problem. Finally, we search the space spectrums to acquire the DOAs for each direct component and multipath component. Comparative simulation tests and analysis prove the effectiveness of the proposed algorithm in estimation accuracy in underdetermined conditions.

DOA estimation of LFM signals based on STFT and multiple invariance ESPRIT

In order to improve the angle measurement precision of LFM signals with a low computational complexity, a direction of arrival (DOA) estimation algorithm STFT-MI-ESPRIT is proposed in this paper. The algorithm is based on short time Fourier transform (STFT) and multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT). Firstly, the STFT of the array element’s output is calculated and the signals are transformed to the time-frequency domain. Then the spatial time-frequency distribution matrix can be obtained through selecting multiple single-source time-frequency points in the time-frequency plane and the signal subspace can also be obtained using Eigen decomposition. Finally, the multiple rotational invariant equation of the array based on STFT is obtained and the closed-form solution is obtained using the multi-least-squares (MLS) criterion. The simulation results show that the proposed algorithm can improve the estimation precision greatly compared with the traditional ESPRIT-like algorithms and its computational complexity remains the same in general. This paper also proposes that the STFT-MI-ESPRIT algorithm can use partial rotational invariances of the array instead of all the rotational invariances, which can reduce the computational complexity on the basis of ensuring the estimation precision basically. The simulation results verify the effectiveness of the conclusion.

Underdetermined DOA Estimation of Quasi-Stationary Signals Using a Partly-Calibrated Array

Quasi-stationary signals have been widely found in practical applications, which have time-varying second-order statistics while staying static within local time frames. In this paper, we develop a robust direction-of-arrival (DOA) estimation algorithm for quasi-stationary signals based on the Khatri–Rao (KR) subspace approach. A partly-calibrated array is considered, in which some of the sensors have an inaccurate knowledge of the gain and phase. In detail, we first develop a closed-form solution to estimate the unknown sensor gains and phases. The array is then calibrated using the estimated sensor gains and phases which enables the improved DOA estimation. To reduce the computational complexity, we also proposed a reduced-dimensional method for DOA estimation. The exploitation of the KR subspace approach enables the proposed method to achieve a larger number of degrees-of-freedom, i.e., more sources than sensors can be estimated. The unique identification condition for the proposed method is also derived. Simulation results demonstrate the effectiveness of the proposed underdetermined DOA estimation algorithm for quasi-stationary signals.

Efficient method of two-dimensional DOA estimation for coherent signals

An effective decoherence method called the fourth-order cumulants-based improved Toeplitz matrices reconstruction (FOC-ITMR) is addressed for two-dimensional (2-D) direction-of-arrival (DOA) estimation of coherent signals. To avoid the loss of the array’s physical aperture, the FOC-ITMR method fully utilizes the information of received data from the whole two parallel uniform linear arrays (ULAs) and the changing reference element based on FOC. Compared with previous works, the proposed method can offer excellent decoherence performance in both white noise and color noise environments. In addition, the proposed algorithm can achieve automatic pair-matching without additional computation. The theoretical analysis and simulation results confirm the effectiveness of the proposed algorithm.

DOA estimation for wideband LFM signals with a few snapshots

The wideband linear frequency modulation (LFM) signals are widely used in information systems. The conventional direction-of arrival (DOA) estimation algorithms of LFM signals rely on a large number of snapshots, some of which are not reliable in numerous practical applications such as underwater array processing. To solve the above problem, we present a modified sparse iterative covariance (MSPICE)-based estimation method in fractional Fourier transform (FrFT) domain to estimate the DOA of wideband LFM signals. First, we extend the original SPICE algorithm in FrFT domain with a specific transform order for wideband LFM signals. Then, we utilize the energy centrobaric modification method to make the original SPICE more accurate without adding more computational complexity. The simulation results demonstrate the effectiveness of the proposed method.

DOA estimation for wideband signals based on weighted Squared TOPS

This paper introduces a new direction-of-arrival (DOA) estimation method for wideband signal sources. The new method estimates the DOA of wideband signal sources based on squared test of orthogonality of projected subspaces (Squared TOPS) which is an improved method of TOPS. TOPS and Squared TOPS use the signal and noise subspaces of multiple frequency components of wideband signal sources. Although coherent wideband method, such as coherent signal subspace method (CSSM), performs high DOA estimation accuracy, it requires the initial estimate of signal source directions. On the other hand, TOPS and Squared TOPS can provide good performance of DOA estimation without the initial value of signal sources; however, some false peaks appear in spatial spectrum based on these methods. The proposed method, called weighted Squared TOPS (WS-TOPS), uses the modified squared matrix and selective weighted averaging process to improve DOA estimation performance. The performance of WS-TOPS is compared with those of TOPS, Squared TOPS, incoherent MUSIC, and test of orthogonality of frequency spaces (TOFS) through computer simulations. The simulation results show that WS-TOPS can suppress all false peaks in spatial spectrum and improve DOA estimation accuracy and also keep the same resolution performance as Squared TOPS.

Computationally Efficient and Noise Robust DOA and Pitch Estimation

Many natural signals, such as voiced speech and some musical instruments, are approximately periodic over short intervals. These signals are often described in mathematics by the sum of sinusoids (harmonics) with frequencies that are proportional to the fundamental frequency, or pitch. In sensor (microphone) array signal processing, the periodic signals are estimated from spatio-temporal samples regarding to the direction of arrival (DOA) of the signal of interest. In this paper, we consider the problem of pitch and DOA estimation of quasi-periodic audio signals. In real-life scenarios, recorded signals are often contaminated by different types of noise, which challenges the assumption of white Gaussian noise in most state-of-the-art methods. We establish filtering methods based on noise statistics to apply to nonparametric spectral and spatial parameter estimates of the harmonics. We design minimum variance solutions with distortionless constraints to estimate the pitch from the frequency estimates, and to estimate the DOA from multichannel phase estimates of the harmonics. Applying this filtering method as the sum of weighted frequency and DOA estimates of the harmonics, we also design a joint DOA and pitch estimator. In white Gaussian noise, we derive even more computationally efficient solutions which are designed using the narrowband power spectrum of the harmonics. Numerical results reveal the performance of the estimators in colored noise compared with the Cramer–Rao lower bound. Experiments on real-life signals indicate the applicability of the methods in practical low local signal-to-noise ratios.

Two-stage DOA estimation of independent and coherent signals in spatially coloured noise

A novel fourth order cumulant-based matrix reconstruction algorithm is presented for direction of arrival (DOA) estimation when both independent and coherent signals coexist in the presence of spatially coloured noise. The method operates in two stages. By exploiting the orthogonality between subspaces, the DOA estimates of uncorrelated sources are first obtained, then the independent components are eliminated by reconstructing the corresponding cumulant matrix. Secondly, a series of matrix reconstructions are performed, then the remaining coherent sources are resolved from the reconstructed matrix which has been rank restored. The resultant algorithm can resolve more signals than array elements with higher accuracy and better classification of signal type than previous methods. Simulation results demonstrate the validity and efficiency of the proposed method.

입사신호의 도래방향 추정을 위한 최대 사후 확률 추정기에 대한 연구

본 연구에서는 균일 선형 배열 안테나 시스템에서 입사신호의 방향을 추정하기 위한 기존의 방법과 제안방법의 성능에 대해서 비교한다. 본 논문에서 제안한 방법은 최대 사후 확률 추정기를 적용하여 신호의 도래방향 추정 오차확률을 감소하고자 한다. 신호 추정 방향 확률 오차를 감소시키면 안테나에 입사하는 신호의 방향을 정확히 추정할 수 있다. 모의실험을 이용하여 본 연구에서 제안한 방법과 기존의 방법을 비교 분석하였으며 또한 배열 안테나 개수를 증가시키면서 신호 추정 오차 확률을 비교 분석하였다. 본 연구에서 제안한 방법이 기존의 방법보다 약 8%의 신호 추정 오차 확률을 감소시켜 도래방향 신호 추정 능력이 우수함을 입증하였다. In this paper, we are comparative analysis both class method and proposal method in order to estimation of incident signal direction on uniform array antenna system. Proposal method of this paper decrease error probability for a signal direction of arrival estimation using maximum posterior probability estimator. If it decrease to signal estimation direction error probability, signal direction of arrival can correctly estimate. Through simulation, we were comparative analysis proposed method and class method. Also, we were comparative analysis about signal estimation error probability with increasing array antenna element. We show the superior performance of the proposed method relative to the class method to decrease of signal estimation error probability about 12%.

PD Source Diagnosis and Localization in Industrial High-Voltage Insulation System via Multimodal Joint Sparse Representation

Partial discharge (PD) is the manifestation of insulation degradation, and it is regarded as a great risk in the field of industrial high-voltage insulation system. In this paper, the direction-of-arrival (DOA) estimation algorithm is used for the localization of partial-discharge source. The intersecting point of two rays, which come from two different directions measured by two uniform linear arrays (ULAs), can be regarded as the plane location of partial-discharge source. Fast rise times of partial-discharge pulses result in a wide electromagnetic spectrum, thus this paper focuses on the DOA estimation of wideband signals. The technique of multimodal joint sparse representation (MJSR) has been used to improve the performance of biometrics recognition. Here, we extend it to DOA estimation. The received data are represented by a sparse linear combination of potential steering vectors, while constraining the observations from different frequencies subject to sharing the same sparsity pattern. Based on the simultaneous orthogonal matching pursuit (SOMP) and alternating direction method of multipliers (ADMM), a hard threshold algorithm is proposed for DOA estimation. In order to reduce the computational complexity of hard threshold algorithm, an improved soft threshold DOA estimation algorithm based on the ADMM is proposed as well. The effectiveness of the proposed algorithms is validated by simulations and real tests.

Robust System Architecture for DOA Estimation based on Total Forward Backward Matrix Pencil Algorithm

Radio Direction Finding (DF) is a technique that identifies the bearing angle or the coordinates of an incoming radio signal(s). The primary function of DF is to get the Direction of Arrival (DOA) information. In this paper, we propose the robust system architecture for DOA estimation using the Total Forward Backward Matrix Pencil Method (TFBMP). This method works directly on signal samples of incoming signals received by an M-element Uniform Linear Antenna (ULA) array. The simulation results for DOA estimation of RF signals using the proposed system will be shown and analyzed to verify its performance.

Direction-of-Arrival Estimation for Radar Ice Sounding Surface Clutter Suppression

Ice sounding radars are able to measure ice sheets by profiling their glaciological features from the surface to the bedrock. The current airborne and, in particular, future space-based systems are suffering from off-nadir surface clutter, which can mask the depth signal of interest. The most recent surface clutter suppression techniques are based on multi-phase-center systems combined with sophisticated coherent postprocessing. The performance of the techniques can be improved by accurate direction-of-arrival (DOA) estimates of the surface clutter. This paper deals with data-driven DOA estimation for surface clutter signals, which includes a formulation of the mathematical foundation of spatial aliasing. DOA estimation is applied to data acquired with the P-band POLarimetric Airborne Radar Ice Sounder at the Jutulstraumen Glacier, Antarctica. The effects of spatial aliasing related to a large phase center spacing are analyzed, and an unwrapping procedure is presented and applied to the data. Finally, DOA estimation of full-scene data is analyzed and used to show an along-track and incidence (off-nadir) angle dependent variation of the effective scattering center of the surface return, which is caused by a varying penetration depth.

Reduced-Dimension Noncircular-Capon Algorithm for DOA Estimation of Noncircular Signals

The problem of the direction of arrival (DOA) estimation for the noncircular (NC) signals, which have been widely used in communications, is investigated. A reduced-dimension NC-Capon algorithm is proposed hereby for the DOA estimation of noncircular signals. The proposed algorithm, which only requires one-dimensional search, can avoid the high computational cost within the two-dimensional NC-Capon algorithm. The angle estimation performance of the proposed algorithm is much better than that of the conventional Capon algorithm and very close to that of the two-dimensional NC-Capon algorithm, which has a much higher complexity than the proposed algorithm. Furthermore, the proposed algorithm can be applied to arbitrary arrays and works well without estimating the noncircular phases. The simulation results verify the effectiveness and improvement of the proposed algorithm.

Broadband DOA Estimation Based on Nested Arrays

Direction of arrival (DOA) estimation is a crucial problem in electronic reconnaissance. A novel broadband DOA estimation method utilizing nested arrays is devised in this paper, which is capable of estimating the frequencies and DOAs of multiple narrowband signals in broadbands, even though they may have different carrier frequencies. The proposed method converts the DOA estimation of multiple signals with different frequencies into the spatial frequency estimation. Then, the DOAs and frequencies are pair matched by sparse recovery. It is possible to significantly increase the degrees of freedom (DOF) with the nested arrays and the number of sources can be more than that of sensor array. In addition, the method can achieve high estimation precision without the two-dimensional search process in frequency and angle domain. The validity of the proposed method is verified by theoretic analysis and simulation results.