scholarly journals Beam-Doppler Unitary ESPRIT for Multitarget DOA Estimation

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Cai Wen ◽  
Yan Zhou ◽  
Mingliang Tao ◽  
Jianxin Wu ◽  
Jinye Peng
Keyword(s):  
Fourier Transform ◽  
Computational Complexity ◽  
Doa Estimation ◽  
Critical Issue ◽  
Radar System ◽  
Estimation Accuracy ◽  
Invariance Property ◽  
Multitarget Tracking ◽  
Numerical Examples ◽  
System A

High-resolution direction of arrival (DOA) estimation is a critical issue for mainbeam multitarget tracking in ground-based or airborne early warning radar system. A beam-Doppler unitary ESPRIT (BD-UESPRIT) algorithm is proposed to deal with this problem. Firstly, multiple snapshots without spatial aperture loss are obtained by using the technique of time-smoothing. Then the conjugate centrosymmetric discrete Fourier transform (DFT) matrix is used to transform the extracted data into beam-Doppler domain. Finally, the rotational invariance property of the space-time beam is exploited to estimate DOA of the target. The DOA estimation accuracy is improved greatly because the proposed algorithm takes full advantage of temporal information of the signal. Furthermore, the computational complexity of the presented algorithm is reduced dramatically, because the degree of freedom after beam transformation is very small and most of the operations are implemented in real-number domain. Numerical examples are given to verify the effectiveness of the proposed algorithm.

scholarly journals DOA Estimation for Sources with Large Power Differences

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qingyuan Fang ◽  
Mengzhe Jin ◽  
Weidong Liu ◽  
Yong Han
Keyword(s):  
Computational Complexity ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Invariant Property ◽  
Large Power ◽  
Diagonal Loading ◽  
Weak Source ◽  
Strong Source ◽  
Cramer Rao Bound

Sources with large power differences are very common, especially in complex electromagnetic environments. Classical DOA estimation methods suffer from performance degradation in terms of resolution when dealing with sources that have large power differences. In this paper, we propose an improved DOA algorithm to increase the resolution performance in resolving such sources. The proposed method takes advantage of diagonal loading and demonstrates that the invariant property of noise subspace still holds after diagonal loading is performed. We also find that the Cramer–Rao bound of the weak source can be affected by the power of the strong source, and this has not been noted before. The Cramer–Rao bound of the weak source deteriorates as the power of the strong source increases. Numerical results indicate that the improved algorithm increases the probability of resolution while maintaining the estimation accuracy and computational complexity.

scholarly journals Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Xinnan Fan ◽  
Linbin Pang ◽  
Pengfei Shi ◽  
Guangzhi Li ◽  
Xuewu Zhang
Keyword(s):  
Genetic Algorithm ◽  
Computational Complexity ◽  
Maximum Likelihood ◽  
Likelihood Function ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Initial Population ◽  
Crossover Operator ◽  
Excellent Performance ◽  
Evolutionary Genetic

The maximum likelihood (ML) method achieves an excellent performance for DOA estimation. However, its computational complexity is too high for a multidimensional nonlinear solution search. To address this issue, an improved bee evolutionary genetic algorithm (IBEGA) is applied to maximize the likelihood function for DOA estimation. First, an opposition-based reinforcement learning method is utilized to achieve a better initial population for the BEGA. Second, an improved arithmetic crossover operator is proposed to improve the global searching performance. The experimental results show that the proposed algorithm can reduce the computational complexity of ML DOA estimation significantly without sacrificing the estimation accuracy.

scholarly journals A Low-Complexity GA-WSF Algorithm for Narrow-Band DOA Estimation

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Haihua Chen ◽  
Jialiang Hu ◽  
Hui Tian ◽  
Shibao Li ◽  
Jianhang Liu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Computational Complexity ◽  
Population Size ◽  
Narrow Band ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Low Complexity ◽  
Estimation Accuracy ◽  
Improved Genetic Algorithm ◽  
Complexity Estimation

This paper proposes a low-complexity estimation algorithm for weighted subspace fitting (WSF) based on the Genetic Algorithm (GA) in the problem of narrow-band direction-of-arrival (DOA) finding. Among various solving techniques for DOA, WSF is one of the highest estimation accuracy algorithms. However, its criteria is a multimodal nonlinear multivariate optimization problem. As a result, the computational complexity of WSF is very high, which prevents its application to real systems. The Genetic Algorithm (GA) is considered as an effective algorithm for finding the global solution of WSF. However, conventional GA usually needs a big population size to cover the whole searching space and a large number of generations for convergence, which means that the computational complexity is still high. To reduce the computational complexity of WSF, this paper proposes an improved Genetic algorithm. Firstly a hypothesis technique is used for a rough DOA estimation for WSF. Then, a dynamic initialization space is formed around this value with an empirical function. Within this space, a smaller population size and smaller amount of generations are required. Consequently, the computational complexity is reduced. Simulation results show the efficiency of the proposed algorithm in comparison to many existing algorithms.

scholarly journals Joint DOA and Polarization Estimation with Two Parallel Sparse Dipole Arrays

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Xie ◽  
Ling Wang ◽  
Zhaolin Zhang
Keyword(s):  
Parameter Estimation ◽  
Mutual Coupling ◽  
Direction Cosine ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Invariance Property ◽  
Array Configuration ◽  
Vector Sensors ◽  
Array Aperture ◽  
Parallel Arrays

Electromagnetic vector sensors (EMVS) have attracted growing attention in recent years. However, the mutual coupling effects in practical EMVS arrays may seriously degrade the parameter estimation performance. In order to solve this problem, a novel array configuration consisting of two parallel sparse dipole arrays is proposed. Based on the spatially rotational invariance property between the two parallel arrays and the interdipole spacing inside each array, highly accurate but ambiguous direction-cosine estimates, coarse direction-of-arrival (DOA) estimates, and polarization parameter estimation can be obtained jointly. The coarse DOA estimates are then employed to disambiguate the phase ambiguities in the fine estimates. Compared with collocated EMVS, the proposed array overcomes the mutual coupling problem. Moreover, the DOA estimation accuracy is promoted due to the sparse array aperture extension. Simulation results demonstrate the effectiveness of the proposed algorithm.

scholarly journals DOA Estimation of Noncircular Signals Using Quaternions

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Tianzhen Meng ◽  
Minjie Wu ◽  
Naichang Yuan
Keyword(s):  
Computational Complexity ◽  
Covariance Matrix ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Estimation Problem ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Output Vector ◽  
Noncircular Signals ◽  
Simulation Results

The two-dimensional (2D) direction-of-arrival (DOA) estimation problem for noncircular signals using quaternions is considered in this paper. In the framework of quaternions, we reconstruct the conjugate augmented output vector which reduces the dimension of covariance matrix. Compared with existing methods, the proposed one has two main advantages. Firstly, the estimation accuracy is higher since quaternions have stronger orthogonality. Secondly, the dimension of covariance matrix is reduced by half which decreases the computational complexity. Simulation results are presented verifying the efficacy of the algorithm.

scholarly journals Estimation of DOA for Noncircular Signals via Vandermonde Constrained Parallel Factor Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Heyun Lin ◽  
Chaowei Yuan ◽  
Jianhe Du ◽  
Zhongwei Hu
Keyword(s):  
Computational Complexity ◽  
Doa Estimation ◽  
Least Square ◽  
Estimation Accuracy ◽  
Tensor Model ◽  
Complete Study ◽  
Noncircular Signals ◽  
Parallel Factor ◽  
Parafac Decomposition ◽  
Extended Matrix

We provide a complete study on the direction-of-arrival (DOA) estimation of noncircular (NC) signals for uniform linear array (ULA) via Vandermonde constrained parallel factor (PARAFAC) analysis. By exploiting the noncircular property of the signals, we first construct an extended matrix which contains two times sampling number of the received signal. Then, taking the Vandermonde structure of the array manifold matrix into account, the extended matrix can be turned into a tensor model which admits the Vandermonde constrained PARAFAC decomposition. Based on this tensor model, an efficient linear algebra algorithm is applied to obtain the DOA estimation via utilizing the rotational invariance between two submatrices. Compared with some existing algorithms, the proposed method has a better DOA estimation performance. Meanwhile, the proposed method consistently has a higher estimation accuracy and a much lower computational complexity than the trilinear alternating least square- (TALS-) based PARAFAC algorithm. Finally, numerical examples are conducted to demonstrate the effectiveness of the proposed approach in terms of estimation accuracy and computational complexity.

Inverse Kinematics of Discretely Actuated Ball-Joint Manipulators Using Workspace Density

2015 ◽  
Author(s):  
Hui Dong ◽  
Taosha Fan ◽  
Zhijiang Du ◽  
Gregory Chirikjian
Keyword(s):  
Fourier Transform ◽  
Computational Complexity ◽  
Inverse Kinematics ◽  
Solution Space ◽  
Rotation Group ◽  
Ball Joint ◽  
End Effector ◽  
Numerical Examples ◽  
One Dimensional ◽  
Elegant Form

We present a workspace-density-based (WSDB) method to solve the inverse kinematics of discretely actuated ball-joint manipulators. Intuitively speaking, workspace density measures the flexibility of a robotic manipulator when the end-effector is fixed at a certain pose or position. We use the SE(3) Fourier transform to derive the workspace density for ball-joint manipulators and show that the workspace density has a concise and elegant form. Then we show that the state for each joint is determined by maximizing the workspace density of subsequent sub-manipulators. We demonstrate our method with several numerical examples. In particular, we show that our method can provide a solution that approximately minimizes the deviation of the end-effector and its computational complexity is linear with respect to the number of joints. Hence our method is very efficient in solving the inverse kinematics of redundant discretely actuated ball-joint manipulators. In addition, we prove that the solution space of our method is reduced from the rotation group SO(3) to a one-dimensional interval.

A Unitary-UCA-Root-MUSIC Algorithm Based on MSWF

2014 ◽  
Vol 610 ◽  
pp. 339-344
Author(s):  
Qiang Guo ◽  
Yun Fei An
Keyword(s):  
Computer Simulation ◽  
Computational Complexity ◽  
Real Time ◽  
Unitary Transformation ◽  
Wiener Filter ◽  
Doa Estimation ◽  
Signal Subspace ◽  
Music Algorithm ◽  
Multi Stage ◽  
Simulation Results

A UCA-Root-MUSIC algorithm for direction-of-arrival (DOA) estimation is proposed in this paper which is based on UCA-RB-MUSIC [1]. The method utilizes not only a unitary transformation matrix different from UCA-RB-MUSIC but also the multi-stage Wiener filter (MSWF) to estimate the signal subspace and the number of sources, so that the new method has lower computational complexity and is more conducive to the real-time implementation. The computer simulation results demonstrate the improvement with the proposed method.

The Fast Diagonal-Matrix-Weight IMM Algorithm for Target Tracking

2012 ◽  
Vol 461 ◽  
pp. 132-137
Author(s):  
Yang Fu ◽  
Ming Wei ◽  
Hai Chuan Zhang ◽  
Liang Gao
Keyword(s):  
Stochastic Process ◽  
Computational Complexity ◽  
Target Tracking ◽  
Real Time ◽  
Probability Density Functions ◽  
Diagonal Matrix ◽  
Estimation Accuracy ◽  
Density Functions ◽  
Alternative Algorithm ◽  
Real Time Application

The diagonal-matrix-weight IMM (DIMM) algorithm can solve the IMM algorithm confusions of probability density functions (PDFs) and probability masses of stochastic process. Combingandfilter，the Fast-IMM algorithm has a better performance both in accuracy and reducing computational complexity. In order to improve the estimation accuracy and computational complexity，we apply Fast-IMM method to DIMM algorithm. Therefore，A new method, Fast diagonal-matrix-weight IMM (fast-DIMM) algorithm, is proposed in this paper to heighten the real-time application of DIMM algorithm. Simulations indicate that the proposed fast-DIMM algorithm is a competitive alternative algorithm to the IMM algorithm in real time application

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