2D MUSIC Research Articles

Distributed Two-Dimensional MUSIC for Joint Range and Angle Estimation with Distributed FMCW MIMO Radars.

To estimate range and angle information of multiple targets, FMCW MIMO radars have been exploited with 2D MUSIC algorithms. To improve estimation accuracy, received signals from multiple FMCW MIMO radars are collected at the data fusion center and processed coherently, which increases data communication overhead and implementation complexity. To resolve them, we propose the distributed 2D MUSIC algorithm with coordinate transformation, in which 2D MUSIC algorithm is operated with respect to the reference radar’s coordinate at each radar in a distributed way. Rather than forwarding the raw data of received signal to the fusion center, each radar performs 2D MUSIC with its own received signal in the transformed coordinates. Accordingly, the distributed radars do not need to report all their measured signals to the data fusion center, but they forward their local cost function values of 2D MUSIC for the radar image region of interest. The data fusion center can then estimate the range and angle information of targets jointly from the aggregated cost function. By applying the proposed scheme to the experimentally measured data, its performance is verified in the real environment test.

Joint Angle, Velocity, and Range Estimation Using 2D MUSIC and Successive Interference Cancellation in FMCW MIMO Radar System

Joint Angle, Velocity, and Range Estimation Using 2D MUSIC and Successive Interference Cancellation in FMCW MIMO Radar System

A Novel High-Resolution Imaging Method Using Reduced-Dimension Beamspace Unitary MUSIC for OFDM-MIMO Radar

Imaging of maneuvering targets has become a challenging topic recently. This study proposes an improved MUSIC-based single-snapshot imaging method for OFDM-MIMO radar. At the transmitter part, for orthogonal waveform generation, the interleaved OFDM structure is developed that each transmitter only radiates at an equidistant set of OFDM subcarriers unique to itself. At the receiver part, a novel preprocessing scheme is presented to separate multiple transmit/receive paths and compensate the reference point. Preprocessed echo matrix can fit the model of two-Dimensional (2D) MUSIC algorithm, except for the coupling between radial/cross-range in the virtual antenna array. Correspondingly, we modify the 2D ElementSpace (ES)-MUSIC. In the meantime, a 2D Reduced-Dimension BeamSpace Unitary-MUSIC (RD-BS-UMUSIC) algorithm is proposed for computational complexity reduction and estimation performance enhancement. Numerical results of a simulated target consists of limited number of scatterers and a complex target (a Boeing 737-800 plane) verify that the proposed algorithm can improve the imaging quality and reduce computational complexity effectively compared with the traditional method.

A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array

Coherent source localization is a common problem in signal processing. In this paper, a sparse representation method is considered to deal with two-dimensional (2D) direction of arrival (DOA) estimation for coherent sources with a uniform circular array (UCA). Considering that objective function requires sparsity in the spatial dimension but does not require sparsity in time, singular value decomposition (SVD) is employed to reduce computational complexity and ℓ2 norm is utilized to renew objective function. After the new objective function is constructed to evaluate residual and sparsity, a second-order cone (SOC) programming is employed to solve convex optimization problem and obtain 2D spatial spectrum. Simulations show that the proposed method can deal with the case of coherent source localization, which has higher resolution than 2D MUSIC method and does not need to estimate the number of coherent sources in advance.

Joint Doppler and DOA estimation using (Ultra-)Wideband FMCW signals

The joint Doppler and Direction-of-Arrival (DOA) estimation of moving targets using an (Ultra-)Wideband (UWB) frequency modulated continuous-wave (FMCW) antenna array radar is investigated. Besides the well-known range migration problem, another concern for wideband signals is the DOA estimation problem. For the first time, both problems are considered in this paper simultaneously, where the wideband DOA is transformed into a second-order coupling system similar to the range migration problem by using the property of the FMCW signal. A novel embedded compensation approach to eliminate the coupling terms caused by range migration and wideband DOA is proposed and 2D multiple signal classification (2D MUSIC) algorithm is subsequently applied with dynamic noise subspace to joint estimation of Doppler and DOA. Further, to reduce the computational load caused by multiple eigendecompositions of large matrices, efficient implementation methods are proposed and their performance in speed, accuracy and robustness is compared. The performance of the proposed methods is validated by the numerical simulations and is compared with Keystone MUSIC. Finally, it is shown that for a small number of targets, the Rayleigh-Ritz is the most efficient approach among them.

Fast algorithm for moving target localisation using FDA‐MIMO radar

Target localisation using frequency diverse array (FDA) has drawn much attention owing to the additional degree of freedom in the range dimension. However, the Doppler effect was often ignored in previous FDA works because of the stationary target assumption, and in contrast, even stationary target localisation could be of quite a high computational complexity. In this study, a method is proposed that can jointly estimate range, angle, and Doppler for FDA multiple-input-multiple-output radar with low computational complexity. First, Doppler is estimated independently by utilising unstructured maximum likelihood method. Next, traditional two-dimensional (2D) MUSIC is divided into multiple one-dimensional (1D) MUSIC to estimate the angle. Then substituting the estimated angle into the former 2D MUSIC results in a 1D searching over range dimension to get the range estimation. The advantage of the proposed method was verified by simulation results.

Taylor expansion MUSIC method for joint DOD and DOA estimation in a bistatic MIMO array

We propose a Taylor expansion multiple signal classification (TE MUSIC) method for joint direction of departure (DOD) and direction of arrival (DOA) estimation in a bistatic multiple-input multiple-output (MIMO) array. First, using a Taylor expansion of the steering vector, a two-dimensional (2D) search in the conventional MUSIC method for MIMO arrays is reduced to a two-step one-dimensional (ID) search in the proposed TE MUSIC method. Second, DOAs of the targets can be achieved via Lagrange multiplier by a ID search. Finally, substituting the DOA estimates into the 2D MUSIC spectrum function, DODs of the targets are obtained by another ID search. Thus, the DOD and DOA estimates can be automatically paired. The performance of the proposed method is better than that of the MIMO ESPRIT method, and is similar to that of the 2D MUSIC method. Furthermore, due to the ID search, the TE MUSIC method avoids the high computational complexity of the 2D MUSIC method. Simulation results are presented to show the effectiveness of the proposed method.

Novel Rank Enhancing Algorithm for 2D Sparse Arrays with Contiguous Coarrays

Sparse array is an irregular array with a high degree of freedom in its difference coarray domain. Nested array and coprime array are two important one dimensional sparse arrays. For fixed number of sensors, nested array has a high degree of freedom, resolution and accuracy than coprime array. 1D nested arrays do not provide 2D scanning. 2D nested array which is an extension of 1D nested array provides both 2D scanning as well as high degree of freedom, however direction of arrival (DoA) estimation techniques used for 2D nested array such as 2D unitary ESPRIT and 2D spatial smoothing MUSIC has high computational complexity. This paper shows that spatial smoothing is not necessary to apply 2D MUSIC in the difference coarray domain of 2D nested array. A new Hermitian Toeplitz matrix is constructed instead of spatial smoothing. 2D MUSIC on this Hermitian Toeplitz matrix can resolve the DoA of sources with less computations.

A Fast Algorithm for 2D DOA Estimation Using an Omnidirectional Sensor Array.

The traditional 2D MUSIC algorithm fixes the azimuth or the elevation, and searches for the other without considering the directions of sources. A spectrum peak diffusion effect phenomenon is observed and may be utilized to detect the approximate directions of sources. Accordingly, a fast 2D MUSIC algorithm, which performs azimuth and elevation simultaneous searches (henceforth referred to as AESS) based on only three rounds of search is proposed. Firstly, AESS searches along a circle to detect the approximate source directions. Then, a subsequent search is launched along several straight lines based on these approximate directions. Finally, the 2D Direction of Arrival (DOA) of each source is derived by searching on several small concentric circles. Unlike the 2D MUSIC algorithm, AESS does not fix any azimuth and elevation parameters. Instead, the adjacent point of each search possesses different azimuth and elevation, i.e., azimuth and elevation are simultaneously searched to ensure that the search path is minimized, and hence the total spectral search over the angular field of view is avoided. Simulation results demonstrate the performance characters of the proposed AESS over some existing algorithms.

Two-Dimensional DOA Estimation Using Arbitrary Arrays for Massive MIMO Systems

With the quick advancement of wireless communication networks, the need for massive multiple-input-multiple-output (MIMO) to offer adequate network capacity has turned out to be apparent. As a portion of array signal processing, direction-of-arrival (DOA) estimation is of indispensable significance to acquire directional data of sources and to empower the 3D beamforming. In this paper, the performance of DOA estimation for massive MIMO systems is analyzed and compared using a low-complexity algorithm. To be exact, the 2D Fourier domain line search (FDLS) MUSIC algorithm is studied to mutually estimate elevation and azimuth angle, and arbitrary array geometry is utilized to represent massive MIMO systems. To avoid the computational burden in estimating the data covariance matrix and its eigenvalue decomposition (EVD) due to the large-scale sensors involved in massive MIMO systems, the reduced-dimension data matrix is applied on the signals received by the array. The performance is examined and contrasted with the 2D MUSIC algorithm for different types of antenna configuration. Finally, the array resolution is selected to investigate the performance of elevation and azimuth estimation. The effectiveness and advantage of the proposed technique have been proven by detailed simulations for different types of MIMO array configuration.

SS-BMUSIC Algorithm for Space-Time 2D Signal Model

This paper presents a beamforming matrix with spatial smoothing effect, and extends it to the space-time 2D signal model, which not only reduces the computational complexity of the space-time 2D MUSIC algorithm and improves the coherence resolution capacity, simulation results show that this algorithm has better performance and effectiveness than MUSIC itself.

EFFICIENT NEURAL NETWORK APPROACH FOR 2D DOA ESTIMATION BASED ON ANTENNA ARRAY MEASUREMENTS

In this paper, we present an e-cient Artiflcial Neural Network (ANN)-based model to estimate both azimuth and elevation arrival angles of a signal source. To achieve this goal, the ANN model is constructed using measurement data obtained by a rectangular antenna array in the space-frequency domain. Unlike classical super- resolution algorithms such as 2D MUSIC, the proposed model is capable to account for imperfections of measurement equipment as well as mutual couplings between array elements. The neural model has been verifled for several angular positions and frequencies. It is shown that the use of ANN model to estimate angular positions of a signal source yields more accurate results when compared to 2D MUSIC. Moreover, the neural model signiflcantly outperforms 2D MUSIC in terms of speed of computation.

연산량 감소를 위한 2D MUSIC 알고리즘 설계

GNSS의 재밍에 대응하는 기법은 입사되는 재밍 전력을 억제하는 항재밍 기법과 재밍신호원의 위치를 찾아내는 재머위치결정 기법이 주로 사용된다. 두 방법 모두 재밍신호의 방향을 탐지해야 하며 일반적으로 대표적인 도래각 결정알고리즘인 MUSIC이 사용된다. 그러나 MUSIC은 높은 분해능을 가짐에도 불구하고 모든 후보각에 대한 검색을 수행하므로 검색시간이 길다는 단점이 있다. 본 논문에서는 MUSIC의 목적함수를 Cholesky 분해를 이용하여 제곱 항들의 합 형태로 나타내고, 목적함수 계산 도중 일부의 합이 이미 기존의 최소값 보다 크면 계산을 중단함으로써 검색속도를 향상시키는 새로운 알고리즘을 제안하였다. 제안한 알고리즘의 동작은 소프트웨어 기반의 모의실험을 통하여 검증하였으며 기존 MUSIC 알고리즘과 비교하여 도래각 추정 성능은 같으나 검색속도가 최대 1.15배 향상됨을 확인하였다. The jamming countermeasures in GNSS includes anti-jamming technique and jammer localization technique. In both techniques, direction of jamming signal is important and generally the MUSIC algorithm is used to find the direction of jamming signal. The MUSIC is super-resolution algorithm for detecting incident direction of signal. But, the search time of MUSIC algorithm is too long because all candidates of incidence angle are searched. This paper proposes the new method that has less computational burdens and therefore faster than the conventional MUSIC algorithm. The proposed method improves performance speed by reducing unnecessary calculations. In the proposed method, the cost function of conventional MUSIC algorithm is decomposed into the sum of squares and if the partial sum of cost function is larger than the minimum cost function so far, then the candidate is rejected and next candidates are searched. If the computed cost function is less than the minimum cost function so far, the minimum cost function so far is replaced with newly computed value. The performance of the proposed method was compared with the conventional MUSIC algorithm using the simulation. The accuracy of the estimaed direction of jamming signal was same as the conventional MUSIC while the search speed of the proposed method was 1.15 times faster than the conventional MUSIC.