Arrival Estimation Algorithm Research Articles

서로소 배열에서 프로퍼게이터 방법 기반의 효율적인 도래각 추정 기법

우리는 서로소 배열 안테나에 기존의 프로퍼게이터 방법을 기반으로 하는 도래각 (DoA; direction of arrival) 추정 알고리즘을 제안한다. 서로소 배열 기법은 도래각 추정 해상도를 증가시키나 복잡도를 상호배열의 크기만큼 증가시킨다. 이러한 복잡도를 감소시키기 위하여 우리는 특이값 분해없이 도래각을 추정하는 프로퍼게이터 방법을 이용하는 방법을 제안한다. 우리는 시뮬레이션을 통해 선형 균일 배열 MUSIC, 선형 균일 배열 프로퍼게이터 방법, 서로소 배열을 이용한 MUSIC과 제안한 방법을 비교 및 분석하여, 우리가 제안한 방법이 복잡도가 훨씬 높은 서로소 배열을 이용한 MUSIC 보다는 약간 낮은 성능을 보이지만 나머지 기법들 보다는 훨씬 우수한 성능을 보임을 관찰한다. In this paper, we propose a computationally efficient direction of arrival (DoA) estimation algorithm based on propagator method with non-uniform array. While the co-prime array techniques can improve the resolution of DoA, they generally lead to high computational complexity as the length of the coarray aperture. To reduce the complexity we use the propagator method that does not require singular value decomposition (SVD). Through simulations, we compare MUSIC with uniform lineary array, propagator method with uniform linear array, MUSIC with co-prime array, and the proposed scheme and observe that the performance of the proposed scheme is significantly better than MUSIC or propagator method with uniform linear array while it is slightly worse than computationally much more expensive co-prime array MUSIC scheme.

DOA estimation via sparse recovering from the smoothed covariance vector

A direction of arrival(DOA) estimation algorithm is proposed using the concept of sparse representation. In particular, a new sparse signal representation model called the smoothed covariance vector(SCV) is established, which is constructed using the lower left diagonals of the covariance matrix. DOA estimation is then achieved from the SCV by sparse recovering, where two distinguished error limit estimation methods of the constrained optimization are proposed to make the algorithms more robust. The algorithm shows robust performance on DOA estimation in a uniform array, especially for coherent signals. Furthermore, it significantly reduces the computational load compared with those algorithms based on multiple measurement vectors(MMVs). Simulation results validate the effectiveness and efficiency of the proposed algorithm.

Direction of arrival estimation using adaptive directional time-frequency distributions

Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performa ...

DOA estimation algorithms for low‐angle targets with MIMO radar

The direction of arrival estimation algorithm for low-angle targets with MIMO radar is discussed, and a novel peaks searching algorithm according to the multipath received signal model is derived. The proposed algorithm, which uses the multipath echo signal power and MIMO radar spatial diversity, can avoid the effects of complex multipath transmitter variable and targets glint. It is illustrated that the algorithm has a better performance with the increase of multipath variable or the transmit antennas. Simulation results verify the usefulness of the algorithm.

A Novel Time of Arrival Estimation Algorithm based on Skewness and Kurtosis

A Novel Time of Arrival Estimation Algorithm based on Skewness and Kurtosis

New direction of arrival estimation of coherent signals based on reconstructing matrix under unknown mutual coupling

A direction of arrival (DOA) estimation algorithm for coherent signals in the presence of unknown mutual coupling is proposed. A group of auxiliary sensors in a uniform linear array are applied to eliminate the effects on the orthogonality of subspaces brought by mutual coupling. Then, a Toeplitz matrix, whose rank is independent of the coherency between impinging signals, is reconstructed to eliminate the rank loss of the spatial covariance matrix. Therefore, the signal and noise subspaces can be estimated properly. This method can estimate the DOAs of coherent signals under unknown mutual coupling accurately without any iteration and calibration sources. It has a low computational burden and high accuracy. Simulation results demonstrate the effectiveness of the algorithm.

2D-DOA estimation of noncircular signals for uniform rectangular array via NC-PARAFAC method

ABSTRACTIn this paper, we propose a two-dimensional direction of arrival (2D-DOA) estimation algorithm for uniform rectangular array via noncircular-parallel factor (NC-PARAFAC) method. Compared to the conventional parallel factor (PARAFAC) algorithm, the proposed algorithm exploits the property of noncircular signals to double the array aperture. Therefore, the angle estimation performance of the proposed algorithm is better than the conventional PARAFAC method. The proposed algorithm achieves automatically paired two-dimensional angle estimates, and has better 2D-DOA estimation performance than some conventional algorithms, which include estimation of signal parameters via rotational invariance technique (ESPRIT), propagator method (PM), PARAFAC algorithm, noncircular-ESPRIT (NC-ESPRIT) and noncircular-PM (NC-PM). We also derive the Cramér–Rao bound for the 2D-DOA estimation of noncircular signals with uniform rectangular array. Simulation results verify the effectiveness and improvement of the proposed algorithm.

Evaluation of performance enhancement on CRLB of CAF under multiple emitters

A method of enhancing performance is described on the Cramer–Rao lower bound (CRLB) of time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements under multiple emitters. The TDOA and FDOA measurements between two receivers can be simultaneously estimated by using the cross ambiguity function (CAF). However, in the case of multiple emitters, these measurements are contaminated by the inter-symbol interferences (ISIs) which deteriorate the estimation quality. Therefore, it is required to reduce the effect of ISIs for enhancing the performance prior to calculating CAF. For separating the interference signals from the desired signal, we select the angle of arrival estimation algorithm with multiple array antennas. The performance of the estimator can be expressed as CRLB and the separation probability is calculated by employing the locally most powerful test. From the numerical evaluation results, it was observed that the performance could be significantly improved especially for the situation under heavy ISIs.

A Novel Time of Arrival Estimation Algorithm based on Energy Detector

Accurate localization has gained significant interest in the field of sensor networks, impulse radio60GHz signals which is low cost, low complexity are even much more practical for ranging, localization and tracking systems because of the high time and multipath resolution and so on. Typically, accurate Time of Arrival (TOA) estimation of the 60GHz signals is very important. In order to improve the precision of the TOA estimation, a new TOA estimation algorithm based on Energy Detector is proposed which is based on a joint metric of the Skewness, Kurtosis, Maximum Slope and Standard Deviation after Energy Detection. The best threshold based on the signal-to-noise ratio (SNR) is investigated and the effects of the integration period and channel model are examined. Simulation results are presented which show that for theIEEE802.15.3c channel models CM1.1 and CM2.1, the proposed algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.

Implementation and Validation of an Angle of Arrival (AoA) Determination System for Real-time on-board Train Positioning

This paper presents the implementation of an Angle of Arrival (AoA) estimation algorithm using FPGA technology as a part of a Smart Train Positioning System (STPS). The STPS takes advantage of the combination of different technologies and techniques, such as GNSS and the AoA of the GSM-R signals, to determine the real time train position. Furthermore, a complete software AoA system simulator has been implemented and used to validate the implementation of the AoA algorithm in the FPGA.

On Dimensions of OTA Setups for Massive MIMO Base Stations Radiated Testing

The development of base stations (BSs) with large aperture antenna arrays, enabled partially by the utilization of cmWave and mmWave frequency bands, will require radiated testing in fading conditions. In this paper, the objective is to investigate the suitable measurement distances and physical dimensions of the over-the-air setups for the performance evaluation of massive multiple-input multiple-output (MIMO) BSs in anechoic chambers with multiple probes. Setup dimension is the major cost factor in the test systems and is thus the key issue to be investigated. The purpose is to determine whether the conventional far field criteria must be followed when determining the range of the setup or if they can be relieved. The impact of limited test setup dimension on various metrics, e.g., far field criteria, field performance within the test area, system link budget analysis, direction of arrival estimation algorithm as well as multi-user MIMO sum-rate capacity are investigated to determine the range of the test setup. It was found that the link budget does not support for the measurement distances claimed by the Fraunhofer distance. Most of the utilized metrics, especially the sum rate capacity, indicate that smaller setup sizes can still yield reasonable measurement accuracy. Simulations were performed at 2.6, 3.5, and 28 GHz frequencies.

Separation and localization of multiple distributed wideband chirps using the fractional Fourier transform

In this paper, we consider the problem of localizing the multiple distributed wideband chirp sources using the fractional Fourier transform. The model in the time domain and that in the fractional Fourier domain derived by the Taylor series expansion are presented respectively. The representation of location vector in the Dechirping domain is illustrated which is only related to the central angle. A novel direction of arrival (DOA) estimation algorithm in the Dechirping domain is proposed, which is extended from the conventional multiple signal classification (MUSIC) algorithm in the time domain. Using this algorithm, except for estimating the DOA, the incidence source number can be determined as well which is allowed to exceed the sensor number in the array. To demonstrate the performance of proposed algorithm, numerical results are conducted. Compared to the previous FrFT-MUSIC algorithm based on the assumption of point source model, the proposed algorithm performs a better estimation performance, especially for large angular spread and low signal-to-noise ratio.

MATLAB Simulation of Subspace based High Resolution Direction of Arrival Estimation Algorithm

MATLAB Simulation of Subspace based High Resolution Direction of Arrival Estimation Algorithm

Modified particle filtering algorithm for single acoustic vector sensor DOA tracking.

The conventional direction of arrival (DOA) estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF) algorithm is proposed with state space model of single acoustic vector sensor. Although the particle filtering (PF) algorithm has been introduced for acoustic vector sensor applications, it is not suitable for the case that one dimension angle of source is estimated with large deviation, the two dimension angles (pitch angle and azimuth angle) cannot be simultaneously employed to update the state through resampling processing of PF algorithm. To solve the problems mentioned above, the MPF algorithm is proposed in which the state estimation of previous moment is introduced to the particle sampling of present moment to improve the importance function. Moreover, the independent relationship of pitch angle and azimuth angle is considered and the two dimension angles are sampled and evaluated, respectively. Then, the MUSIC spectrum function is used as the “likehood” function of the MPF algorithm, and the modified PF-MUSIC (MPF-MUSIC) algorithm is proposed to improve the root mean square error (RMSE) and the probability of convergence. The theoretical analysis and the simulation results validate the effectiveness and feasibility of the two proposed algorithms.

A Two-Stage Detection Method for Moving Targets in the Wild Based on Microphone Array

Target detection is an important issue in the unattended ground sensors. In this paper, inspired by the idea of subspace-based direction of arrival estimation algorithms, a new target detection algorithm called subspace-based target detection (SBTD) is proposed to detect moving targets. The SBTD employs the SNR of the acoustic signals to decide whether moving targets are exiting or not. Although the SBTD has good detection performance, its cost maybe a little high for unattended sensors with low-cost hardware and long-term monitoring. To relieve the cost, we propose the hierarchical detection scheme and develop a two-stage detection method based on the SBTD for target detection in the wild, in which the first stage detection algorithm is chosen from current detection algorithms, while the second stage detection algorithm employs the SBTD. Experiments are conducted to verify the proposed detection method through acoustic signals gathered by the micro-electro-mechanical systems (MEMS) microphone array in the wild. Results show that the detector constructed by our two-stage detection method cannot only estimate the SNR of the acoustic signals but also can reduce the false alarm rate significantly with the detection rate almost unchanged in comparison with the detector chosen by its first-stage detection algorithm. The results indicate that a better detection performance is achieved in terms of the receiver operator characteristic curves.

Subspace‐based DOA estimation with sliding signal‐vector construction for ULA

Recently, various subspace-based direction of arrival (DOA) estimation algorithms have been proposed that do not require the computationally expensive eigen-decomposition or singular value decomposition process. In particular, a recently proposed algorithm based on the cross-correlation matrix between data vectors collected by the component uniform linear arrays (ULAs) of an L-shaped array is reported as providing the best performance with the least complexity among such algorithms. Proposed is an algorithm based on the autocorrelation matrix of the data vector collected by a single ULA and methods are proposed to further improve performance with a minimal increased in complexity.

이동 물체의 잡음과 간섭제거를 위한 신호 부 공간기법에 대한 연구

In this paper, we study the method for desired signals estimation that array antennas are received signals. We apply sub spatial method of direction of arrival algorithm and adaptive array antennas in order to remove interference and noise signal of received antenna signals. Array response vector of adaptive array antenna is probability, it is correctly estimation of direction of arrival of targets to update weight signal. Desired signals are estimated updating covariance matrix after moving interference and noise signals among received signals. We estimate signals using eigen decomposition and eigen value, high resolution direction of arrival estimation algorithm is devided signal sub spatial and noise sub spatial. Though simulation, we analyze to compare proposed method with general method.

Joint for time of arrival and direction of arrival estimation algorithm based on the subspace of extended hadamard product

In the joint estimation for time of arrival (TOA) and direction of arrival (DOA) in the narrow-band orthogonal frequency division multiplexing (OFDM) system with antenna arrays, the estimation accuracy is not high in the situation of few numbers of arrays. Especially, DOA cannot be estimated if the number of multiple paths is more than that of the arrays. For these problems, a joint estimation algorithm for TOA and DOA based on the subspace of the extended hadamard product is proposed. First of all, the algorithm constructs an extended channel response in frequency domain via channel estimation for each array in the frequency domain. Then, auto-correlation matrix of extended channel response in the frequency domain is estimated by sampling many times. This estimation method of channel response in the frequency domain can use the fast Fourier transform algorithm. And the hadamard product in the extended noise subspace is obtained by eigenvalue decomposition. Finally, the pseudo-spectral function is constructed and used to search for spectrum peaks, so as to realize the joint estimation of TOA and DOA. The proposed algorithm requires no parameter paring but needs a two-dimensional searching. Monte Carlo algorithm can be used to reduce computational complexity. Simulation results show that the root mean square error of the joint TOA and DOA estimation which can be matched automatically is closer to the Cramer-Rao bound than that using present algorithms. And the proposed algorithm can be still applied when the number of multiple paths is more than number of arrays.

Frequency Domain Extended-MUSIC Algorithm for TOA Estimation in Indoor UWB Radio Impulse Channels

indoor localization systems have grown considerably, in order to obtain a high performance in dense multipath propagation channels. Many studies have been done in this area. Different methods have been proposed based on the use of Impulse Radio Ultra Wide band (IR-UWB) signals. These systems are usually based on time of arrival estimation using different algorithms. In this paper, a new time of arrival estimation algorithm is proposed for impulse radio UWB systems, which is based on the EXTENDED-MUSIC algorithm. Furthermore, Simulation results show these performances in multipath channels. The proposed method is compared with other high resolution algorithms such as Multiple SIGNAL Classification (MUSIC), estimation of signal parameters via rotational invariance technique (ESPRIT) and the MATRIX PENCIL method. Simulation will justify the high accuracy and resolution localization capabilities of the proposed algorithm. KeywordsRadio Ultra Wide band (IR-UWB), Time of arrival estimation (TOA), EXTENDED-MUSIC, ESPRIT, MATRIX PENCIL

The influence of random element displacement on DOA estimates obtained with (Khatri-Rao-)root-MUSIC.

Although a wide range of direction of arrival (DOA) estimation algorithms has been described for a diverse range of array configurations, no specific stochastic analysis framework has been established to assess the probability density function of the error on DOA estimates due to random errors in the array geometry. Therefore, we propose a stochastic collocation method that relies on a generalized polynomial chaos expansion to connect the statistical distribution of random position errors to the resulting distribution of the DOA estimates. We apply this technique to the conventional root-MUSIC and the Khatri-Rao-root-MUSIC methods. According to Monte-Carlo simulations, this novel approach yields a speedup by a factor of more than 100 in terms of CPU-time for a one-dimensional case and by a factor of 56 for a two-dimensional case.