Weixian Liu

Chaotic phase code for radar pulse compression

This paper presents a novel binary phase coding scheme for radar pulse compression, which is derived from the logistic-map equation in the chaotic theory. The proposed logistic-map-based binary phase code (LMBPC) makes it feasible to achieve superior performance in detection range. The logistic-map equation in the chaotic theory is range resolution and Doppler tolerance simultaneously. The properties of LMBPC, including autocorrelation function, ambiguity diagram, performance under various noisy backgrounds, and the maximum Doppler tolerance, have been analyzed and compared to those of the conventional schemes, such as linear FM. The properties of LMBPC are very similar to those of the random binary codes. However, the generation of LMBPC is much simpler, and the available LMBPC is virtually infinite and not limited by the length of code. A parallel correlator structure for the pulse compression filter has also been introduced, which serves to improve the Doppler tolerance.

Empirical mode decomposition of micro-Doppler signature

Micro-Doppler induced by mechanical vibration or rotation of structures in a radar target is potentially useful for target detection, classification and recognition. In order to exploit the time-varying micro-Doppler signature, time frequency analysis techniques are used. However, they can not represent this useful information clearly all the time. In this paper, we introduce a novel algorithm to extract the micro-Doppler signature using a technique called empirical mode decomposition. Both simulation and the experimental results indicate that EMD provides us an effective way to give better time frequency representation of the micro-Doppler signature.

Data fusion of multiradar system by using genetic algorithm

Detection system with distributed sensors and data fusion. are increasingly being used by surveillance systems. There has been a great deal of theoretical study on decentralized detection networks composed of identical or non-identical sensors. To solve the resulting nonlinear system, exhaustive search and some crude approximations are adopted. However, those methods often cause either the system to be insensitive to some parameters or the suboptimal results. In this paper, a novel flexible genetic algorithm is investigated to obtain the optimal results on constant false alarm rate data fusion. Using this approach, all system parameters are directly coded in decimal chromosomes and they can be optimized simultaneously. The simulation results show that adopting the proposed approach, one can achieve better performances than the reported methods and results.

A new approach for ground moving target indication in foliage environment

Ground moving target indication (GMTI) in foliage environment is a challenging problem, because the strong echoes from dense foliage environment and big attenuation of the radar microwave often make it difficult for traditional time frequency distributions to clearly and locally represent the Doppler frequency. This paper introduced a new approach to improve the performance of GMTI. This so-called Hilbert Huang Transform (HHT) method composes of empirical mode decomposition (EMD) and Hilbert transform technique. EMD is applied to extract target signal from interference and the associated Hilbert transform calculates the instantaneous Doppler frequency, representing a novel Hilbert spectrum in time frequency domain. Both simulative and experimental signals are used to validate the efficiency of HHT. This adaptive approach offers higher signal to disturbance ratio and higher resolution in the time frequency distribution.

A novel approach for CFAR processors design

Two novel constant false alarm rate (CFAR) detectors, the And-CFAR and Or-CFAR, are proposed, The two new CFAR detectors improve the conventional cell averaging CFAR (CA-CFAR) and order statistics CFAR (OS-CFAR) by making full use of the cell information. The novel CFAR processors combine the result of the CA-CFAR and OS-CFAR to get a better detection performance. In a homogeneous background, the mathematical medals of the two new CFAR detectors are derived and their performance has been evaluated and compared with that of CA-CFAR and OS-CFAR.

Low frequency radar phenomenology study in equatorial vegetation

This paper presents a study based on field measurements on several equatorial foliage penetration phenomena in Singapore. The study includes short-range back scattering and propagation measurements in a very wide frequency band from 100 MHz to 1 GHz. The measurement setup and the data analysis are presented.

preliminary results

Distributed order statistics constant false alarm rate (OS-CFAR) detection techniques are important for nonstationary observation with varying weak narrowband random signals. However, it is very difficult to choose system parameters to obtain optimal threshold values because of the nonlinear property of the distributed OS-CFAR detection system. This paper provides a novel solution based on an effective and flexible genetic algorithm. Using this approach, all system parameters are directly coded in decimal chromosomes and they can be optimized simultaneously. The simulation results show that using the proposed approach one can achieve better performances than the reported methods and results. Furthermore, our method can also be used for more general nonhomogeneous situations with different fusion rules.

A novel threshold optimization for distributed OS-CFAR of multistatic radar systems by using the genetic algorithm

Abstract One-dimension range profile can reflect the precise geometric structure features of radar targets. The approach is comprehensively used for radar target identification (RTI), however it varies with target posture. This paper presents a novel neural network model—linear interpolation neural network (LINN) to solve the problem. LINN combines the variation information of one-dimension range profile with its invariant feature information. Simulation results show that this method greatly improves the target identification performance of radar systems.

One-dimension range profile identification of radar targets based on a linear interpolation neural network

This paper presents an analytical model for a single folded loop antenna with detection coverage in three dimensions of space. Based on the antenna theory, the inductance and impedance of the loop antenna is investigated. The electromagnetic simulation is used to determine proper antenna topology for optimal performance. The proposed design is implemented as a RFID reader antenna on the industry inventory control and supply chain application.

RFID high frequency 3-dimensional loop antenna analysis and design

The matched filter has been implemented on TI TMS320C6201 Evaluation Module (EVM) digital signal processing board as a part of a linear FM radar receiver. Both time and frequency domain techniques were applied for implementation. The optimal processing speed has been achieved by fully exploiting the capacities of the EVMs 8 independent functional units. Simulations have been carried out using Signal Processing Workbench (SPW) prior to implementation to verify the algorithms.