Institute of Information and Navigation

Fengcheng, China

Institute of Information and Navigation

Fengcheng, China
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Bai J.,Institute of Information and Navigation | Xia J.,Institute of Information and Navigation | Wu J.,Air Force Dalian Communications Noncommissioned Officers School | Lu C.,Unit 95806
Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology | Year: 2015

An online anomaly detection algorithm based on incremental projective non-negative matrix factorization is proposed to detect the network anomaly real-timely and efficiently. Firstly, an incremental projective non-negative matrix factorization is given, which has the same expression with PCA, and is able to construct normal and abnormal subspace to detect network-wide anomalies online by Shewhart control chart. Theoretic analysis indicates that, the proposed algorithm computation is far smaller than NMF-NAD. In addition, traffic matrix datasets analyzing for internet and simulation results show that the network anomalies detection algorithms based on NMF(such as NMF-NAD and ODA-IPNMF) performs better than that based on PCA, and the proposed ODA-IPNMF has comparable network anomaly detection by NMF-NAD, which the ability to detect the network anomaly online. ©, 2015, Harbin Institute of Technology. All right reserved.


Deng D.-H.,Institute of Information and Navigation | Zhu X.-P.,Institute of Information and Navigation | Zhang Q.,Institute of Information and Navigation | Zhang Q.,Fudan University | And 2 more authors.
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2012

In the bistatic ISAR systems, in order to solve the problems of weak scatters detection and identification in strong noise background, the stochastic resonance(SR) was applied to extract the information of weak scatters. On the assumption that the strong scatters could be detected, the signals after de-chirp were disposed through transformation in fast time axis firstly, which made the signals satisfy the condition of adiabatic approximation;then the SR was used to detect the signal frequency that expressed the instantaneous range difference;after that, some processing were implemented to confirm the right positions of weak scatters and to improve the output signal-noise-ratio(SNR). Numerical simulations shows that the SR can improve the SNR largely and enlarge the dynamic bound of radar receiver.


Zhu F.,Institute of Information and Navigation | Zhu F.,No 93508 Unit Of Pla | Zhang Q.,Institute of Information and Navigation | Luo Y.,Institute of Information and Navigation | And 3 more authors.
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2013

On the basis of the frequency spectrogram synthesis theory with orthogonal frequency division-linear frequency modulation (OFD-LFM) signal and the single snapshot imaging theory of Mingle-Input Multiple-Output (MIMO) high-resolution radar are analyzed, the united sparsity model with frequency spectrogram sparsity for OFD-LFM signal and space field sparsity for MIMO radar antenna array is given. Sparsity processing method based on Compressed Sensing (CS) theory is proposed, which can synthesize high-resolution range profile (HRRP) and image target. The high quality HRRP and two dimension image of target can be obtained with single snapshot by using the proposed sparse imaging method, on condition of the sub-frequency number in OFD-LFM signal is reduced, the receiver number of MIMO high-resolution radar is dimensioned apparently. Further, the problem of movement compensation due to target maneuver is avoided, the method is benefit for realizing the antenna array arrangement. Simulation results show that the proposed method is effective and robust for anti-noise.


Li M.,Institute of Information and Navigation | Xiong W.,Institute of Information and Navigation | Liang Q.,Xi'an Institute of Post and Telecommunications
Chinese Journal of Sensors and Actuators | Year: 2013

An improved intelligent DV-Hop algorithm is proposed in order to solve the problem of the poor locating performance when using multilateral measurement method for computing the coordinates of unknown nodes in the range-free DV-Hop algorithm for Wireless Sensor Network (WSN). Firstly, the node localization problem was transformed into a global optimization problem based on analyzing the theory of multilateral measurement method with DV-Hop algorithm. Then according to the superiority on solving the optimization problem, Adaptive Artificial Bee Colony (AABC) algorithm was proposed by considering the specific localization problem. Finally, the improved ABC algorithm was used at the stage of location in DV-Hop algorithm so as to accomplish the localization. The results from simulation show that compared with multilateral measurement method and DV-Hop algorithm based on original ABC algorithm, and under the circumstances of different number of beacon ratio and different number of nodes, applying the improved DV-Hop algorithm, better locating performance precision and precision stability can be achieved obviously.

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