No abstract

No abstract

An advanced source number estimation (SNE) algorithm based on both fuzzy C-means clustering (FCM) and data local density (DLD) is proposed in this paper. The DLD of an eigenvalue refers to the number of eigenvalues within a specific neighborhood of this eigenvalue belonging to the data covariance matrix. This local density essentially as the one-dimensional sample feature of the FCM is extracted into the SNE algorithm based on FCM and can enable to improve the probability of correct detection (PCD) of the SNE algorithm based on the FCM especially for low signal-to-noise ratio (SNR) environment. Comparison experiment results demonstrate that compared to the SNE algorithm based on the FCM and other similar algorithms, our proposed algorithm can achieve highest PCD of the incident source number in both cases of spatial white noise and spatial correlation noise.

Aiming at the problems of the WPKI certificate verification schemes based on online certificate status protocol (OCSP), this paper proposes a WPKI certificate verification scheme based on the certificate digest signature-online certificate status protocol (CDS OCSP). Compared with the existing schemes, the proposed scheme optimizes the number of communication connections between the communication entities and the network, reduces the consumption of the wireless network bandwidth in the certificate verification process, and uses the elliptic curves cipher-(ECC-) based encrypting/decrypting functions to sign and verify the certificate digest, which ensures the consistency of the verified certificates among the communication entities. The proposed scheme makes the certificate verification process more efficient and secure. The experimental results show that the proposed scheme effectively reduces the communication consumption of the wireless network and saves the storage space of the wireless entities.

No abstract

No abstract

No abstract

Currently for the polarization vector array of unknown noise covariance matrix still use scalar matrix model, resulting in low precision of source number estimation Estimation and a series of problems. This paper defines the polarization sensitive array under unknown correlated noise field of the noise covariance matrix, it is derived under the assumption that the spatial noise covariance is block diagonal or banded, covariance matrix of the original noise model is modified. Three models are compared based on scalar matrix, polarization sensitive vector array, modified polarization array vector array underlying unknown correlated noise field. The simulation results of MATLAB show that the correct detection probability of the modified model can be significantly improved. Furthermore the analysis of noise suppression is envisaged due to the fact that modified noise covariance matrix has Toeplitz structure. 