Time–frequency (TF) approaches are frequently employed for source localization at low signal to noise ratio. However, TF approaches fail to achieve the desired performance for sparsely sampled signals or signals corrupted by heavy noise in an under-determined scenario when sources are not TF separable. In this study, we propose a new TF method for direction of arrival (DOA) estimation of sources with closely spaced and overlapping TF signature. The proposed method uses a combination of a high-resolution time–frequency distribution and instantaneous frequency estimation method for extraction of sources with intersecting and closely spaced time–frequency signatures. Once sources are extracted, their DOAs are estimated using a well known multiple signal classification (MUSIC) algorithm. Experimental results demonstrate that the proposed source localization method achieves better performance as compared to the conventional time–frequency MUSIC algorithm.
相似文献In this paper, we address the joint estimation of doubly selective channels (DSCs) and carrier frequency offsets (CFOs) in multiple input multiple output orthogonal frequency division multiple access uplink with highly mobile users. Since the channel coefficients are rapidly varying over time and the base station has to perform the estimation task from the received composite signal, the exact solution to this joint estimation problem requires multidimensional search which is computationally intensive. We propose an iterative technique for the joint estimation of DSCs and CFOs based on space alternating generalized expectation maximization algorithm which will decompose the multidimensional optimization to many one dimensional searches. The proposed method works even in the presence of residual timing offsets and it does not require the knowledge of channel statistics at the receiver. Convergence properties of the proposed algorithm in terms of rate matrix is studied and analytically proved that the proposed joint estimation algorithm converges. Simulation studies illustrate that the proposed technique offers good performance even at very high mobile speeds.
相似文献As the problem of array mixing model of wideband signals cannot be solved by conventional blind source separation algorithms, an improved algorithm based on beamforming is proposed in this paper. First, the received signals are transformed into time–frequency domain, and the delays of source signals are estimated. Then, the received signals are compensated with the estimated delay in frequency domain. Finally, the desired signal is acquired by using Frost wideband beamforming algorithm. Due to adopting the new methods of single source point extraction and delay estimation, the complexity of the proposed algorithm is reduced. Pre-steering delay is used in frequency domain to eliminate the compensation error when the delay is not an integer multiple of the sampling interval, which improves the separation performance significantly. The simulation results show that the proposed algorithm can adequately solve the problem of delay mismatch and achieve wideband blind source separation effectively. The existing algorithms are mostly fail for frequency hopping signals when there are numerous overlapping time–frequency points. In this case, the proposed algorithm still has good separation performance.
相似文献This paper is concerned with the estimation of the directions-of-arrival (DOA) of multiple linear chirp signals. We construct a novel time-frequency dictionary based on the properties of chirp signals in the fractional Fourier domain, and a sparse reconstruction algorithm is proposed to achieve high performance. Then, the errors resulting from the off-grid model mismatch is considered, and the dictionary matrix is reformulated into a multiplication of a fixed matrix and a sparse matrix. Further, an iterative alternating approach is proposed to improve the accuracy of the DOA estimates. The proposed algorithm provides better estimation, anti-correlation performances and increased resolution than Multiple Signal Classification (MUSIC) and the time–frequency MUSIC (TF-MUSIC) based on the spatial time–frequency distributions. Simulation results demonstrate the effectiveness of the proposed approach.
相似文献Wireless communication systems utilizing orthogonal frequency division multiplexing (OFDM) transmissions are capable of delivering high data rates over multipath frequency selective channels. This paper deals with joint estimation/interpolation of wireless channel using pilot symbols transmitted concurrently with the data. We propose a low complexity, spectrally efficient minimum mean square error channel estimator which exploits the correlation structure of channel frequency response for reducing the complexity. Specifically, it is shown that if pilots are inserted appropriately across OFDM subcarriers, the proposed algorithm requires no matrix inversion, thereby significantly relieving the computational burden without deteriorating the performance. Moreover, the knowledge of channel correlation is also not required for the proposed estimator. Simulation results validate that the proposed technique outperforms existing low-complexity variants in terms of mean square error and computational complexity.
相似文献In this paper an adaptive optimized fast blind channel estimation using cyclic prefix supported with Space Time Block Coded Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (STBC-MIMO-OFDM) system is presented. The main aspire of our technique is to support multiple users at the same time over same frequency band based on the Multi-Carrier Code-Division Multiple Access (MC-CDMA) approach. High complexity and low convergence is the main obstacle in earlier blind channel estimation techniques. Modified flower pollination algorithm is implemented to overcome this problem. The MC-CDMA approach is utilized to implement the blind channel estimation. The proposed MC-CDMA is used to reduce the error rate included in the Blind Channel Estimation. As a part of wireless communications, time block coding technique is utilized to transmit several copies of information across the number of antennas. To develop the consistency of data transfer different received data is used and then MFPA results in lower fuel cost compared to FPA. MFPA produces better results compared with previous methods.
相似文献We use one vector and two pressure sensors to form a sparse large aperture L-shape array for high performance two-dimensional (2D) direction of arrival (DOA) and frequency estimation. Because the number of sensors is small and there is only one vector sensor in the presented array, thus, the installation of sensors in the array is simpler and installation error is smaller, than the conventional array. Meanwhile, a high performance 2D DOA and frequency estimation method is presented. Firstly, utilizing single vector sensor and based on the ESPRIT, a group coarse 2D DOA and frequency parameters are obtained. Secondly, to restrain space noise or interference, a matrix filter is utilized to process the covariance matrix which comes from sensor array, so as to form a new covariance matrix which possesses high signal to noise ratio. Thirdly, utilizing the new covariance matrix and based on the ESPRIT again, accurate but ambiguity angles estimates are obtained. Fourthly, one signal power estimator and one optimization method are presented to solve the angle ambiguity and frequency ambiguity problems, respectively. The proposed method gains a high performance 2D DOA and frequency estimation results. Numerical simulations are performed to verify the feasibility of the proposed method.
相似文献