A Low-Complexity Algorithm for Coherent DOA Estimation in Monostatic MIMO Radar

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.

Download Full-text

Low-complexity ESPRIT-based DOA estimation for colocated MIMO radar using reduced-dimension transformation

Electronics Letters ◽

10.1049/el.2010.3279 ◽

2011 ◽

Vol 47 (4) ◽

pp. 283 ◽

Cited By ~ 61

Author(s):

X. Zhang ◽

D. Xu

Keyword(s):

Doa Estimation ◽

Low Complexity ◽

Mimo Radar ◽

Reduced Dimension

Download Full-text

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

Mathematical Problems in Engineering ◽

10.1155/2013/427980 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 3

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.

Download Full-text

Computationally Efficient DOA Tracking Algorithm in Monostatic MIMO Radar with Automatic Association

International Journal of Antennas and Propagation ◽

10.1155/2014/501478 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 7

Author(s):

Huaxin Yu ◽

Xiaofei Zhang ◽

Xueqiang Chen ◽

Hailang Wu

Keyword(s):

Array Signal Processing ◽

Tracking Error ◽

Multiple Input Multiple Output ◽

Doa Estimation ◽

Low Complexity ◽

Mimo Radar ◽

Tracking Algorithm ◽

Computationally Efficient ◽

Input Multiple Output ◽

The Difference

We consider the problem of tracking the direction of arrivals (DOA) of multiple moving targets in monostatic multiple-input multiple-output (MIMO) radar. A low-complexity DOA tracking algorithm in monostatic MIMO radar is proposed. The proposed algorithm obtains DOA estimation via the difference between previous and current covariance matrix of the reduced-dimension transformation signal, and it reduces the computational complexity and realizes automatic association in DOA tracking. Error analysis and Cramér-Rao lower bound (CRLB) of DOA tracking are derived in the paper. The proposed algorithm not only can be regarded as an extension of array-signal-processing DOA tracking algorithm in (Zhang et al. (2008)), but also is an improved version of the DOA tracking algorithm in (Zhang et al. (2008)). Furthermore, the proposed algorithm has better DOA tracking performance than the DOA tracking algorithm in (Zhang et al. (2008)). The simulation results demonstrate effectiveness of the proposed algorithm. Our work provides the technical support for the practical application of MIMO radar.

Download Full-text

A low complexity algorithm for DOA estimation based on reduced-rank covariance matrix

2014 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) ◽

10.1109/icspcc.2014.6986152 ◽

2014 ◽

Cited By ~ 1

Author(s):

Yuanming Guo ◽

Wei Li ◽

Junyuan Shen ◽

Xuezhen Xu ◽

Jinjun Zhang ◽

...

Keyword(s):

Covariance Matrix ◽

Doa Estimation ◽

Low Complexity ◽

Reduced Rank ◽

Complexity Algorithm

Download Full-text

Sound source location for low-altitude aircraft based on sub-band extraction

MATEC Web of Conferences ◽

10.1051/matecconf/202133601004 ◽

2021 ◽

Vol 336 ◽

pp. 01004

Author(s):

Junwen Zhu ◽

Ruixia Cheng ◽

Jiawei Li ◽

Yu Tian ◽

Yiwen Zhang

Keyword(s):

Wide Band ◽

Doa Estimation ◽

Low Complexity ◽

Spatial Spectrum ◽

Spectrum Simulation ◽

Combination Principle ◽

Simulation Results ◽

Low Altitude ◽

The Cost ◽

Complexity Algorithm

The acoustic signal of low-altitude aircraft shows regular distribution in frequency and has obvious harmonic crest of both fundamental frequency and double frequency.Therefore, this paper presents a low complexity algorithm of acoustic location based on feature sub-band extraction for low-altitude aircraft. The algorithm firstly searches the eigenfrequency points which occupy the main energy in the sound signal. Then the cost function is constructed based on the MUSIC method by the sub-band corresponding to the eigenfrequency point. Finally, the amplitude is weighted by the maximum ratio combination principle to obtain the spectral function of array space, by which DOA estimation is realized for the spatial spectrum. Simulation results show that the algorithm is less complex than traditional wide-band DOA algorithm, and its main lobe is easier to recognize and has better spatial resolution.

Download Full-text