Monostatic surface wave radar is vulnerable by the threat of stealth targets and establishment of near space bistatic radar is the most achievable way to solve this problem. The positioning principle and accuracy in near space bistatic radar is discussed in this paper. The geometrical dilution of precision expression of single measurement subset is calculated. The position precision contours of measurement subsets are obtained and which subset can be chosen for positioning at different area is pointed out. Simulation results show that different subset has different position accuracy and a high accuracy subset distributing picture is presented. Research of this paper provides a theoretical base of detecting and tracking for near space bistatic radar.
An intrusion detection method based on RS-LSSVM is studied in this paper. Firstly, attribute reduction algorithm based on the generalized decision table is proposed to remove the interference features and reduce the dimension of input feature space. Then the classification method based on least square support vector machine (LSSVM) is analyzed. The sample data after dimension reduction is used for LSSVM training, and the LSSVM classification model is obtained, which forms the ability of detecting unknown intrusion. Simulation results show that the proposed method can effectively remove the unnecessary features and improve the performance of network intrusion detection.
<p>As the sensing element and a driving element for vibration control using smart materials, the structural vibration control is very active field for research and application. This paper mainly study the characteristics of piezoelectric self-sensing vibration .Through the action analysis of research on Piezoelectric Actuator establish a self-sensing piezoelectric vibration damper and a model of self-sensing piezoelectric absorber . Then through the experiment and simulation, get the study on its characteristics.</p>
The optimal deployment model and algorithm for near space bistatic radar network are discussed in this paper. Firstly, the coverage rate is analyzed, and the optimal deployment model is established. Then, the standard particle swarm algorithm is improved. Initial position and velocity of every particle are created by the chaos algorithm, and the individual and global extremes are disturbed with some probability in the optimization, which are advantageous in achieving a faster and globalized search of particles. Finally, the improved particle swarm algorithm is used to solve the optimal deployment issue. Simulation results demonstrate the validity of the proposed model and algorithm.
Traditional methods regard coverage area of radar network as the union of every radar’s coverage area. Aiming at this issue, the relationship among radar detection range, radar cross section, signal-to-noise ratio, detection probability and false alarm probability is analyzed. Detection probability model for single radar is established. Calculation method of detection probability for radar network is also researched. Coverage area of radar network can be obtained according to the detection probability. Simulation results show coverage area of radar network is not simply the union of every radar’s coverage area and it is decided by the detection probability. Research of this paper provides a theoretical base of detecting, tracking and placement for radar network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.