Xiaojun Liu

Ionospheric ionogram denoising based on Robust Principal Component Analysis

This paper proposes a preprocess optimization analysis called Robust Principal Component Analysis (RPCA) to eliminate the noises of ionospheric ionograms. Through the theoretical analysis of the basic principle and validity of this method and simulation results, we point out the feasibility of this method and give a useful algorithm named accelerated proximal gradient method (APGp) to solve this RPCA problem. Finally, we verify the feasibility of this method by some simulation results.

An efficient and low-complexity through wall moving target tracking algorithm by UWB radar

Efficient detection and tracking of moving target hidden by walls is of interest for rescue, surveillance and security operations. However, in the process of real-time tracking, there are usually some wrong target locations - noise points in the tracking trajectory. This paper gives a short overview of the complete tracking process with all required phases of radar signal processing. Then the paper focus on the tracking phase and a threshold filter for real-time measurement with low computational complexity is introduced for target tracking. It will be shown by some real data acquired from UWB radar that the use of this new filter can efficiently remove the noise points therefore provide good smoothing of the target trajectory.

Non-destructive survey of pavement layer thicknesses with ground penetrating radar

In pavement survey engineering, ground penetrating radar (GPR) is an effective and non-destructive survey method, compared with traditional core drilling method. Dielectric constant and layer thickness can be acquired from inversion analysis of the GPR signals. In this paper, metal reflection method and a layer picking algorithm called trace correlation are combined to estimate pavement layer thickness rapidly and efficiently. Highway testing shows this survey approach gives small errors, and meets the pavement survey requirements.

On Sparse MIMO Planar Array Topology Optimization for UWB Near-Field High-Resolution Imaging

An optimization method for ultrawideband multiple-input-multiple-output (MIMO) planar array topology design, which can satisfy both uniformity and lower element shadowing principles, is proposed by extending our previous work. Two planar MIMO arrays, namely, the basic optimal array (BOA) and the extended optimal array (EOA) are optimized. The focusing and sidelobe-suppression properties of the BOA and the EOA are demonstrated to be superior to other two previous state-of-the-art planar MIMO arrays. The advantages of the two optimized arrays in 3-D imaging are further indicated by experimental results for different distributed targets. The validity of the proposed method is verified by the excellent performances of the BOA and the EOA.