A new method uses a linear array that takes advantage of underwater physical sound fields to estimate the velocity of an underwater moving target. The mathematical model was established by considering the geometric re...A new method uses a linear array that takes advantage of underwater physical sound fields to estimate the velocity of an underwater moving target. The mathematical model was established by considering the geometric relationship between the moving target installed with only two transducers to radiate sound of different frequencies and the linear array. In addition, deterministic maximum likelihood and signal phase matching algorithms were introduced to effectively find the directions of arrival （DOAs） of the sound sources of the two transducers installed on the target. Factors causing velocity measurement errors were considered. To track the target, a linear array with a compass, a pressure transducer, a signal conditioner and a digital recorder was configured. Relevant requirements for the array parameters were derived. The simulation showed that a 16-element array with an aperture of less than lm can measure velocity with relative error of no more＇, than 4% when including typical system errors. Anechoic pool and reservoir experiments confirmed these results.展开更多
To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. ...To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).展开更多
In multi-LFM signal condition, Radon-Ambiguity Transform (RAT) of the strong LFM component has strong suppression effect on that of the weak LFM component. A method named as Recursive Filtering RAT (RFRAT) algorithm i...In multi-LFM signal condition, Radon-Ambiguity Transform (RAT) of the strong LFM component has strong suppression effect on that of the weak LFM component. A method named as Recursive Filtering RAT (RFRAT) algorithm is proposed for solving this problem. By fully using of the Maximum Likelihood (ML) estimation value of the frequency modulation rate got by RAT, RFRAT can detect the noisy multi-LFM signals out step by step. The merit of this new method is validated by an illustrative example in low Signal-to-Noise-Ratio (SNR) condition.展开更多
This paper proposes an efficient approximate Maximum Likelihood (ML) detection method for Multiple-Input Multiple-Output (MIMO) systems,which searches local area instead of exhaustive search and selects valid search p...This paper proposes an efficient approximate Maximum Likelihood (ML) detection method for Multiple-Input Multiple-Output (MIMO) systems,which searches local area instead of exhaustive search and selects valid search points in each transmit antenna signal constellation instead of all hy-perplane. Both of the selection and search complexity can be reduced significantly. The method per-forms the tradeoff between computational complexity and system performance by adjusting the neighborhood size to select the valid search points. Simulation results show that the performance is comparable to that of the ML detection while the complexity is only as the small fraction of ML.展开更多
基金Supported by the National Science Foundation of China under Grant No.60672136
文摘A new method uses a linear array that takes advantage of underwater physical sound fields to estimate the velocity of an underwater moving target. The mathematical model was established by considering the geometric relationship between the moving target installed with only two transducers to radiate sound of different frequencies and the linear array. In addition, deterministic maximum likelihood and signal phase matching algorithms were introduced to effectively find the directions of arrival （DOAs） of the sound sources of the two transducers installed on the target. Factors causing velocity measurement errors were considered. To track the target, a linear array with a compass, a pressure transducer, a signal conditioner and a digital recorder was configured. Relevant requirements for the array parameters were derived. The simulation showed that a 16-element array with an aperture of less than lm can measure velocity with relative error of no more＇, than 4% when including typical system errors. Anechoic pool and reservoir experiments confirmed these results.
基金supported by Joint Foundation of and China Academy of Engineering Physical (10676006)
文摘To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).
基金Supported by the National 973 Program(No.973-1-12)
文摘In multi-LFM signal condition, Radon-Ambiguity Transform (RAT) of the strong LFM component has strong suppression effect on that of the weak LFM component. A method named as Recursive Filtering RAT (RFRAT) algorithm is proposed for solving this problem. By fully using of the Maximum Likelihood (ML) estimation value of the frequency modulation rate got by RAT, RFRAT can detect the noisy multi-LFM signals out step by step. The merit of this new method is validated by an illustrative example in low Signal-to-Noise-Ratio (SNR) condition.
文摘This paper proposes an efficient approximate Maximum Likelihood (ML) detection method for Multiple-Input Multiple-Output (MIMO) systems,which searches local area instead of exhaustive search and selects valid search points in each transmit antenna signal constellation instead of all hy-perplane. Both of the selection and search complexity can be reduced significantly. The method per-forms the tradeoff between computational complexity and system performance by adjusting the neighborhood size to select the valid search points. Simulation results show that the performance is comparable to that of the ML detection while the complexity is only as the small fraction of ML.
