Guohua Wei

Design and Implementation of an IP-Based Intelligent Video Surveillance System

Rapid advances in digital video coding and networking make it now economically and technically feasible to construct and deploy large scale video surveillance systems. In companion with this it is necessary to make the system more intelligent to assist the operators in scene analysis and event classification. This paper discusses the design and implementation issues of an IP-based intelligent video surveillance system. A system framework for large scale video surveillance is presented and analyzed. Several critical component technologies for such a system are also introduced with some preliminary development results

Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array.

This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile’s rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm.

ISAR imaging of high-speed moving targets in short-range using impulse radar

In order to improve the measurement accuracy of weapons, ultra-wideband (UWB) inverse synthetic aperture radar (ISAR) imaging of high-speed moving targets in short-range is studied. In the scheme, because the positions of scatters vary with the radar line-of-sight (LOS) angle when the high-speed target is passing through the closest point of the approach, the concept of equivalent scattering point (ESP) is proposed. The Hough transform is employed to implement ESP motion parameter estimation, while the target translational motion is compensated by using the ESP time delay, and the angle spanned by the target is estimated by utilizing geometric relationship of ESP motion. Finally, the two-dimensional image of the target is restructured by using the near field time-domain back-projection algorithm. Simulation results confirm that the proposed method is efficient.

Chirp parameter estimation from tensor decomposition

The non-stationary properties of chirp signals restrict the application of the parameter estimation algorithms of single-frequency signals in the scene of chirp signals, simultaneously the traditional chirp parameter estimation algorithms also have limitations, to overcome some of the limitations this paper proposes a new algorithm which can estimate chirp parameter from tensor decomposition. The new algorithm uses the received discrete data aligning according to a certain form to build multidimensional data structures and then applies the tensor decomposition in chip parameter estimation using the shift invariance of subspace, the algorithm provides a new way of thinking in the field of chirp parameter estimation and it can apply in the scene of multiple chirp signals, the simulations prove the effectiveness of the algorithm.

The research of short-range moving target 3-D ISAR imaging

Inverse synthetic aperture radar is widely used for radar imaging of targets, such as aircrafts, ships, missiles and so on. Conventional 2-D ISAR imaging can only obtain the projection in the range-Doppler plane. It cannot get the actual physical size and relative position of the scatter. Whats more, in the traditional ISAR imaging radar system, the target is located in the far-field region. This paper presents a short-range moving target 3-D ISAR imaging method. By using the wavefront reconstruction algorithm, we can get the 2-D image of the target, and then through the interferometric processing of two ISAR images, the third dimension coordinate information is obtained. Simulation results show the feasibility of the algorithm.

Parallel Implementation of Motion Parameters Estimation Algorithm

The motion parameters estimation of the moving target is a key problem in radar signal process. Recently, in order to increase the accuracy of estimation parameters, the technology of modern signal process is used in radar signal process with the cost of increase of computational complexity. So the technology of distributed technology based on the multiprocessor computers is introduced into the field of radar signal process, which improves the compute performance greatly. The design details of the parallel algorithm of motion parameters estimation are addressed from the design, software structure of and adaption. And it was realized with the help of MATLAB distributed computing toolbox.

Application of parallel PSO algorithm to motion parameter estimation

A new method with an efficient parallel particle swarm optimization (PSO) algorithm is proposed for estimating motion parameters. Compared with the traditional methods, modified parallel PSO algorithm features such as easily realizing in parallel machines and ability of global search are demonstrated. The experiments give the performance of algorithm, which could satisfy the desire in the system of flight path estimation.