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Zhang M.,Electronic Engineering Institute of the PLA | Zhang M.,Key Laboratory of Electronic Restricting Technique | Li X.-H.,Electronic Engineering Institute of the PLA | Li X.-H.,Key Laboratory of Electronic Restricting Technique
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | Year: 2014

A novel approach of blind identifying of binary linear block code based on association rules is proposed. This method makes full use of the correspond relationship between each information bits to its parity check bits of the binary block code. If the inner correspond relationship of a binary sequence can be found by association rules, the linear block code of the sequence is correctly recognized. Firstly, the binary sequence is arranged to a matrix, then the matrix is divided into two parts. Therefore, each row of the matrix are becoming two items and two itemsets of the matrix are obtained. After that, the support and confidence of each itemset are calculated. According to the characteristics of the relationship of each information bits to its parity check bits of the binary block code, the linear block code is identified by traversing the way of finding the maximum confidence and the minimum mapping types. As only two parts of the matrix is concerned, the computing complexity of the association rule is degrade greatly. Compared with other methods, the association method is suitable for low error rate of the sequence. Simulation results show that the proposed method has some strong points as high robustness, effectiveness and high accurate recognition, which indicate that the method has a certain value in future engineering application. Source


Yin H.B.,Electronic Engineering Institute | Yin H.B.,Key Laboratory of Electronic Restricting Technique | Yang J.A.,Electronic Engineering Institute | Yang J.A.,Key Laboratory of Electronic Restricting Technique | And 3 more authors.
Applied Mechanics and Materials | Year: 2014

Compressed Sensing is very efficient in reducing the relatively high sampling rate. But when it comes to the channel estimation of uncooperative communication, the common CS reconstruction algorithms seem impractical to implement since a pilot is required, which is difficult for uncooperative communication. In this paper, we combine the sparsity transform dictionary, which is formed by a sequence of delays of the template signal, together with the idea of alternative minimization to improve the traditional CoSaMP algorithm to reconstruct under-sampled UWB-2PPM signal transmitted by unkown complex channel without a knowledge of pilot. The theoretical analysis and simulations show that the proposed algorithm is capable of reconstructing the original transmitted signal without a pilot. © (2014) Trans Tech Publications, Switzerland. Source


Zhang M.,Electronic Engineering Institute | Zhang M.,Key Laboratory of Electronic Restricting Technique | Luo Z.,Electronic Engineering Institute | Luo Z.,Key Laboratory of Electronic Restricting Technique
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2012

A new method for passive cross location based on received signal strength (RSS) is proposed, which can eliminate ghosts under complicated electromagnetic environment. The relationship between array manifold and received signal strength of covariance matrix estimation is derived. Using the high order power of inverse spatial covariance matrix to get noise subspace, the received signal strength is obtained under the condition of known signal directions. From the knowledge of radio prorogation theory, the confidence of each cross location is computed by the relationship between received power and propagation decay. Through this way, the ghosts of cross location are estimated. The simulation results confirm the feasibility and effectiveness of the proposed method, which is robust to angle deviation and low SNR. Source


Li P.-F.,Electronic Engineering Institute of Hefei | Li P.-F.,Key Laboratory of Electronic Restricting Technique | Zhong Z.-F.,Electronic Engineering Institute of Hefei | Zhong Z.-F.,Key Laboratory of Electronic Restricting Technique | And 2 more authors.
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | Year: 2012

Two novel DOA (Direction Of Arrival) estimation methods are proposed using sparse representation when the signal number is unknown. One is the method using sparse representation based on the eigenvector of covariance matrix. The biggest eigenvector of covariance matrix is proved to be the linear combination of all steer vectors and is extracted to build sparse representation model for DOA estimation. The other is the method using sparse representation of high-order power of covariance Matrix. This method approximates the signal sub-space through the high order power of the spatial covariance matrix on the basic of signal eigenvalue being larger than noise eigenvalue. Then the column vector of high order power of the spatial covariance matrix is extracted to construct the sparse representation model for DOA estimation. The theoretical analysis and experimental results show the two methods have a better performance than the MUSIC algorithm in the aspects of accuracy, resolution and adaptability to coherent signals without estimating the number of signals. Source


Luo Z.,Electronic Engineering Institute | Luo Z.,Key Laboratory of Electronic Restricting Technique | Zhang M.,Electronic Engineering Institute | Zhang M.,Key Laboratory of Electronic Restricting Technique | And 2 more authors.
Yuhang Xuebao/Journal of Astronautics | Year: 2013

The power information and the theory of radio propagation are introduced to the direction data association in passive cross location system, a novel data association algorithm based on received signal power estimation is proposed. The relationship between array manifold and received signal strength of covariance matrix estimation is derived. The high order power of inverse spatial covariance matrix is used to approximate the signal subspace, and the received signal power is obtained under the condition of known signal directions, thus avoiding the amplitude-attribute data association algorithm's disadvantage caused by the uncertainty noise and signal wave. The confidence level of each cross location is computed by using the relationship between the received power and the propagation decay. Through this way, the correct association is selected from the set of candidates. The simulation results confirm feasibility and superiority of the proposed method. Source

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