scholarly journals Fast Estimation Method of Space-Time Two-Dimensional Positioning Parameters Based on Hadamard Product

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Haiwen Li ◽  
Nae Zheng ◽  
Xiyu Song ◽  
Yinghua Tian
Keyword(s):  
Frequency Domain ◽  
Orthogonal Frequency Division Multiplexing ◽  
Hadamard Product ◽  
Estimation Method ◽  
Space Time ◽  
Joint Estimation ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Fast Estimation ◽  
Response Vector

The estimation speed of positioning parameters determines the effectiveness of the positioning system. The time of arrival (TOA) and direction of arrival (DOA) parameters can be estimated by the space-time two-dimensional multiple signal classification (2D-MUSIC) algorithm for array antenna. However, this algorithm needs much time to complete the two-dimensional pseudo spectral peak search, which makes it difficult to apply in practice. Aiming at solving this problem, a fast estimation method of space-time two-dimensional positioning parameters based on Hadamard product is proposed in orthogonal frequency division multiplexing (OFDM) system, and the Cramer-Rao bound (CRB) is also presented. Firstly, according to the channel frequency domain response vector of each array, the channel frequency domain estimation vector is constructed using the Hadamard product form containing location information. Then, the autocorrelation matrix of the channel response vector for the extended array element in frequency domain and the noise subspace are calculated successively. Finally, by combining the closed-form solution and parameter pairing, the fast joint estimation for time delay and arrival direction is accomplished. The theoretical analysis and simulation results show that the proposed algorithm can significantly reduce the computational complexity and guarantee that the estimation accuracy is not only better than estimating signal parameters via rotational invariance techniques (ESPRIT) algorithm and 2D matrix pencil (MP) algorithm but also close to 2D-MUSIC algorithm. Moreover, the proposed algorithm also has certain adaptability to multipath environment and effectively improves the ability of fast acquisition of location parameters.

scholarly journals Three-Dimensional Target Localization and Cramér-Rao Bound for Two-Dimensional OFDM-MIMO Radar

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Xingxing Li ◽  
Dangwei Wang ◽  
Xiaoyan Ma
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Mimo Radar ◽  
Joint Estimation ◽  
Target Localization ◽  
Two Dimensional ◽  
Frequency Diversity ◽  
Cramer Rao Bound

Target localization using a frequency diversity multiple-input multiple-output (MIMO) system is one of the hottest research directions in the radar society. In this paper, three-dimensional (3D) target localization is considered for two-dimensional MIMO radar with orthogonal frequency division multiplexing linear frequency modulated (OFDM-LFM) waveforms. To realize joint estimation for range and angle in azimuth and elevation, the range-angle-dependent beam pattern with high range resolution is produced by the OFDM-LFM waveform. Then, the 3D target localization proposal is presented and the corresponding closed-form expressions of Cramér-Rao bound (CRB) are derived. Furthermore, for mitigating the coupling of angle and range and further improving the estimation precision, a CRB optimization method is proposed. Different from the existing methods of FDA-based radar, the proposed method can provide higher range estimation because of multiple transmitted frequency bands. Numerical simulation results are provided to demonstrate the effectiveness of the proposed approach and its improved performance of target localization.

scholarly journals Joint High-Resolution Range and DOA Estimation via MUSIC Method Based on Virtual Two-Dimensional Spatial Smoothing for OFDM Radar

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Rui Zhang ◽  
Ying-Hui Quan ◽  
Sheng-Qi Zhu ◽  
Lei Yang ◽  
Ya-chao Li ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
High Resolution ◽  
Orthogonal Frequency Division Multiplexing ◽  
Doa Estimation ◽  
Joint Estimation ◽  
Two Dimensional ◽  
Spatial Smoothing ◽  
Multiple Signal Classification ◽  
Band Signal ◽  
Angle Parameter

For the purpose of target parameter estimation of the orthogonal frequency-division multiplexing (OFDM) radar, a high-resolution method of joint estimation on range and direction of arrival (DOA) based on OFDM array radar is proposed in this paper. It begins with the design and analysis of an echo model of OFDM array radar. Since there is no coupling between range and angle parameter estimation for a narrow-band signal, a method which exploits the data of one snapshot to estimate the range and angle of the target by means of multiple signal classification (MUSIC) based on virtual two-dimensional spatial smoothing in range and angle dimensions is devised. The proposed method is capable of joint estimating the range and DOA of the target in a high resolution under a single snapshot circumstance. Simulation experiments demonstrate the validity of the proposal.

scholarly journals Computationally Efficient Ambiguity-Free Two-Dimensional DOA Estimation Method for Coprime Planar Array: RD-Root-MUSIC Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Luo Chen ◽  
Changbo Ye ◽  
Baobao Li
Keyword(s):  
Degrees Of Freedom ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Computationally Efficient ◽  
Music Algorithm ◽  
Estimation Algorithms ◽  
Planar Array ◽  
2D Doa Estimation

While the two-dimensional (2D) spectral peak search suffers from expensive computational burden in direction of arrival (DOA) estimation, we propose a reduced-dimensional root-MUSIC (RD-Root-MUSIC) algorithm for 2D DOA estimation with coprime planar array (CPA), which is computationally efficient and ambiguity-free. Different from the conventional 2D DOA estimation algorithms based on subarray decomposition, we exploit the received data of the two subarrays jointly by mapping CPA to the full array of the CPA (FCPA), which contributes to the enhanced degrees of freedom (DOFs) and improved estimation performance. In addition, due to the ambiguity-free characteristic of the FCPA, the extra ambiguity elimination operation can be avoided. Furthermore, we convert the 2D spectral search process into 1D polynomial rooting via reduced-dimension transformation, which substantially reduces the computational complexity while preserving the estimation accuracy. Finally, numerical simulations demonstrate the superiority of the proposed algorithm.

scholarly journals Efficient Joint Estimation of Carrier Frequency and Sampling Frequency Offsets for MIMO-OFDM ATSC Systems

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 554 ◽  
Author(s):  
Yong-An Jung ◽  
Young-Hwan You
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Mean Squared Error ◽  
Estimation Method ◽  
Multipath Fading ◽  
Sampling Frequency ◽  
Joint Estimation ◽  
Estimation Accuracy ◽  
Multipath Fading Channel ◽  
Mimo Ofdm ◽  
Frequency Offsets

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is appealing for the provision of high spectral efficiency in digital terrestrial broadcast systems. To fully obtain its advantageous features, it is very important to remove the frequency mismatch between the transmitter and the receiver. In this paper, we present the performance analysis of joint estimation of carrier and sampling frequency offsets in the MIMO-OFDM-based advanced television systems committee (ATSC) 3.0 system. In the MIMO-OFDM ATSC system, the continual pilot (CP) is primarily utilized to perform frequency synchronization. To efficiently suppress an unwanted bias introduced by the presence of random-likely located CPs, an optimal pilot subset is selected to form the basis of least squares frequency-offset estimation. A closed-form mean squared error is derived in the context of MIMO-OFDM, considering the multipath fading channel. We show via computer simulations and numerical analysis that the proposed estimation method achieves higher estimation accuracy than the existing estimation method.

A Two Dimension Signal Parameter Estimation Method Based on Super Resolution Technology

2013 ◽  
Vol 712-715 ◽  
pp. 2007-2014
Author(s):  
Ying Xu ◽  
Jun Zhao
Keyword(s):  
Signal Processing ◽  
Parameter Estimation ◽  
Array Signal Processing ◽  
Estimation Method ◽  
Super Resolution ◽  
Parameters Estimation ◽  
Joint Estimation ◽  
Spectrum Estimation ◽  
Processing Parameter ◽  
Music Algorithm

The 2D spectrum estimation based on uniform linear array is studied in this paper. MUSIC method is firstly introduced into array signal processing to realize the frequency and angle joint estimation. And the modified MUSIC method is then applied for two dim array signal processing to fulfill joint parameters estimation of coherent signal sources. Simulation results show the validity of the proposed method. Keywords: Super resolution;Array signal processing;Parameter estimation;MUSIC algorithm

Improving Space-Time-Frequency MIMO-OFDM with ICI Self-Cancellation Scheme using Least Square Error Estimator

2015 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Nur Farahiah Ibrahim ◽  
Zahari Abu Bakar ◽  
Azlina Idris
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Symbol Error Rate ◽  
Space Time ◽  
Least Square ◽  
Error Estimator ◽  
Frequency Diversity ◽  
Time Frequency ◽  
Mimo Ofdm ◽  
Subcarrier Mapping

Channel estimation techniques for Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on comb type pilot arrangement with least-square error (LSE) estimator was investigated with space-time-frequency (STF) diversity implementation. The frequency offset in OFDM effected its performance. This was mitigated with the implementation of the presented inter-carrier interference self-cancellation (ICI-SC) techniques and different space-time subcarrier mapping. STF block coding in the system exploits the spatial, temporal and frequency diversity to improve performance. Estimated channel was fed into a decoder which combined the STF decoding together with the estimated channel coefficients using LSE estimator for equalization. The performance of the system was compared by measuring the symbol error rate with a PSK-16 and PSK-32. The results show that subcarrier mapping together with ICI-SC were able to increase the system performance. Introduction of channel estimation was also able to estimate the channel coefficient at only 5dB difference with a perfectly known channel.

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