scholarly journals Scalable ESPRIT Processor for Direction-of-Arrival Estimation of Frequency Modulated Continuous Wave Radar

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 695
Author(s):  
Yongchul Jung ◽  
Hohyub Jeon ◽  
Seongjoo Lee ◽  
Yunho Jung
Keyword(s):  
Continuous Wave ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Array Antenna ◽  
Jacobi Method ◽  
Eigenvalue Decomposition ◽  
Wave Radar ◽  
Hardware Description ◽  
Antenna Configuration ◽  
Esprit Algorithm

The estimation of signal parameters via rotational invariance techniques (ESPRIT) is an algorithm that uses the shift-invariant properties of the array antenna to estimate the direction-of-arrival (DOA) of signals received in the array antenna. Since the ESPRIT algorithm requires high-complexity operations such as covariance matrix and eigenvalue decomposition, a hardware processor must be implemented such that the DOA is estimated in real time. Additionally, the ESPRIT processor should support a scalable number of antenna configuration for DOA estimation in various applications because the performance of ESPRIT depends on the number of antennas. Therefore, we propose an ESPRIT processor that supports two to eight scalable antenna configuration. In addition, since the proposed ESPRIT processor is based on multiple invariances (MI) algorithm, it can achieve a much better performance than the existing ESPRIT processor. The execution time is reduced by simplifying the Jacobi method, which has the most significant computational complexity for calculating eigenvalue decomposition (EVD) in ESPRIT. Moreover, the ESPRIT processor was designed using hardware description language (HDL), and an FPGA-based verification was performed. The proposed ESPRIT processor was implemented with 10,088 slice registers, 18,207 LUTs, and 80 DSPs, and the slice register, LUT, and DSP were reduced by up to 71.45%, 54.5%, and 68.38%, respectively, compared to the existing structure.

scholarly journals Low-Complexity MUSIC-Based Direction-of-Arrival Detection Algorithm for Frequency-Modulated Continuous-Wave Vital Radar

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4295 ◽  
Author(s):  
Bong-seok Kim ◽  
Youngseok Jin ◽  
Jonghun Lee ◽  
Sangdong Kim
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Continuous Wave ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Field Of View ◽  
Music Algorithm ◽  
Trade Offs

This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30°, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment.

scholarly journals Reduced-Complexity Direction of Arrival Estimation Using Real-Valued Computation with Arbitrary Array Configurations

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Feng-Gang Yan ◽  
Jun Wang ◽  
Shuai Liu ◽  
Yi Shen ◽  
Ming Jin
Keyword(s):  
State Of The Art ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Eigenvalue Decomposition ◽  
Music Algorithm ◽  
New Approach ◽  
Multiple Signal Classification ◽  
Wide Range ◽  
Complexity Algorithm

A low-complexity algorithm is presented to dramatically reduce the complexity of the multiple signal classification (MUSIC) algorithm for direction of arrival (DOA) estimation, in which both tasks of eigenvalue decomposition (EVD) and spectral search are implemented with efficient real-valued computations, leading to about 75% complexity reduction as compared to the standard MUSIC. Furthermore, the proposed technique has no dependence on array configurations and is hence suitable for arbitrary array geometries, which shows a significant implementation advantage over most state-of-the-art unitary estimators including unitary MUSIC (U-MUSIC). Numerical simulations over a wide range of scenarios are conducted to show the performance of the new technique, which demonstrates that with a significantly reduced computational complexity, the new approach is able to provide a close accuracy to the standard MUSIC.

scholarly journals Two-Dimensional Direction-of-Arrival Estimation for Trilinear Decomposition-Based Monostatic Cross MIMO Radar

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Fangqing Wen ◽  
Gong Zhang
Keyword(s):  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Mimo Radar ◽  
Eigenvalue Decomposition ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Trilinear Decomposition ◽  
Signal Covariance Matrix

A low complexity monostatic cross multiple-in multiple-out (MIMO) radar scheme is proposed in this paper. The minimum-redundancy linear array (MRLA) is introduced in the cross radar to improve the efficiency of the array elements. The two-dimensional direction-of-arrival (DOA) estimation problem links to the trilinear model, which automatically pairs the estimated two-dimensional angles, requiring neither eigenvalue decomposition of received signal covariance matrix nor spectral peak searching. The proposed scheme performs better than the uniform linear arrays (ULA) configuration under the same conditions, and the proposed algorithm has less computational complexity than that of multiple signal classification (MUSIC) algorithm. Simulation results show the effectiveness of our scheme.

scholarly journals A Robust Direction of Arrival Estimation Method for Uniform Circular Array

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4427
Author(s):  
Xu ◽  
Wu ◽  
Yu ◽  
Guang
Keyword(s):  
Array Signal Processing ◽  
Linear Array ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Circular Array ◽  
Source Signal ◽  
Random Sample Consensus ◽  
Esprit Algorithm ◽  
Source Signals

Estimating the Direction of Arrival (DOA) is a basic and crucial problem in array signal processing. The existing DOA methods fail to obtain reliable and accurate results when noise and reverberation occur in real applications. In this paper, an accurate and robust estimation method for estimating the DOA of sources signal is proposed. Incorporating the Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm with the RANdom SAmple Consensus (RANSAC) algorithm gives rise to the RAN-ESPRIT method, which removes outliers automatically in noise-corrupted environments. In this work, a uniform circular array (UCA) is converted into a virtual uniform linear array (ULA) to begin with. Then, the covariance matrix of the received signals of the virtual linear array is reconstructed, and the ESPRIT algorithm is deployed to estimate initial DOA of the source signal. Finally, the modified RANSAC method with automatically selected thresholds is used to fit the source signal to obtain accurate DOA. The proposed method can remove the unreliable DOA feature data and leads to more accuracy of DOA estimation of source signals in reverberation environments. Experimental results demonstrate that the proposed method is more robust and efficient compared to the traditional methods (i.e., ESPRIT, TLS-ESPRIT).

Two-Dimensional DOA Estimation for Planar Array Using a Successive Propagator Method

2019 ◽  
Vol 28 (10) ◽  
pp. 1950161 ◽  
Author(s):  
Weiyang Chen ◽  
Xiaofei Zhang ◽  
Chi Jiang
Keyword(s):  
Computational Cost ◽  
Doa Estimation ◽  
Rotational Invariance ◽  
Eigenvalue Decomposition ◽  
Invariance Property ◽  
Two Dimensional ◽  
Propagator Method ◽  
Planar Array ◽  
Esprit Algorithm ◽  
Better Than

We consider the problem of two-dimensional (2D) direction of arrival (DOA) estimation for planar array, and propose a successive propagator method (PM)-based algorithm. The rotational invariance property of the propagator matrix is exploited to obtain the initial angle estimations, while the accurate estimates can be achieved through successive one-dimensional and local spectrum-peak searches. The proposed algorithm can obtain automatically paired 2D-DOA estimations, and it requires no eigenvalue decomposition of the covariance matrix of received data, which remarkably reduces the computational cost compared with traditional 2D-PM algorithm. In addition, the DOA estimation performance of the proposed algorithm is better than estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm and PM algorithm, and is close to 2D-PM algorithm which requires 2D spectrum-peak search. Numerical simulations demonstrate the effectiveness and improvement of the proposed algorithm.

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