Ground Penetrating Radar : Theory and Applications

BasicMethods for c-Means Clustering- Variations and Generalizations - I- Variations and Generalizations - II- Miscellanea- Application to Classifier Design- Fuzzy Clustering and Probabilistic PCA Model- Local Multivariate Analysis Based on Fuzzy Clustering- Extended Algorithms for Local Multivariate Analysis

Algorithms for fuzzy clustering : methods in c-means clustering with applications

Time-varying characteristics analysis of vehicle-bridge interaction system based on modified S-transform reassignment technique

GPR image analysis to locate water leaks from buried pipes by applying variance filters

The accurate estimation of GPR migration velocity and comparison of imaging methods

Ensemble empirical mode decomposition (EEMD) is a noise-assisted analysis method, which can overcome the mode mixing problem in empirical mode decomposition (EMD) However, the choice of signal intrinsic mode functions (IMFs) still depends on subjective experience in most cases In order to solve the problem, a noise suppression method based on EEMD and permutation entropy (PE) is proposed according to the characteristics of ground-penetrating radar (GPR) signal In the proposed method, first EEMD is used to decompose the GPR signal into a series of IMFs, and the PE of each IMF is calculated; then, the global threshold obtained by the second-order difference of PE of all IMFs is used to distinguish between noise IMFs and target IMFs; finally, the signal is reconstructed with target IMFs to remove the noise The experimental results for synthetic and practical GPR data show that the proposed method can effectively remove the noise in the GPR signal and improve the resolution of the target

A Noise Suppression Method of Ground Penetrating Radar Based on EEMD and Permutation Entropy

The analysis of ground penetrating radar signal based on generalized S transform with parameters optimization

Principal component analysis is usually used for clutter suppression of ground penetrating radar, but its performance is influenced by the selection of main components of target signal. In the paper, an improved principal component selection rule is proposed for selecting the main components of target signal. In the method, firstly difference spectrum of singular value is used to extract direct wave and strong target signal, and then, Fuzzy-C means clustering algorithm is used to determine the weights of principal component of weak target signal. Finally, the principal components of strong target signal and weak target signal are reconstructed to obtain target signal. Experimental results show that the proposed method can effectively remove the clutter signals and reserve more target information.

A Clutter Suppression Method Based on Improved Principal Component Selection Rule for Ground Penetrating Radar

The invention discloses a parameter optimization based time frequency analysis method for an improved generalized S-transform. The parameter optimization based time-frequency analysis method comprises the steps of firstly selecting the range of parameters in the improved generalized S-transform; for each group of parameters, calculating time frequency distribution of an input signal by using the improved generalized S-transform and carrying out energy normalization processing on the time frequency distribution; then calculating the corresponding time frequency aggregation degree of each group of parameters and employing one group of parameters corresponding to maximum values as optimized parameters; finally introducing the optimized parameters into the improved generalized S-transform to calculate the time frequency distribution of the input signal. According to the parameter optimization based time frequency analysis method for the improved generalized S-transform, a first-order function with frequency as an independent variable is introduced into a window function of the S-transform so that the form of the window function is flexible and adjustable, the parameters of the first-order function are optimized through the time frequency aggregation degree, the energy aggregation of the signal time frequency distribution can be improved, the estimated accuracy of signal instantaneous parameters is enhanced, the calculated amount is small, the parameter optimization based time frequency analysis method is suitable for analysis and processing of communication, radar, earthquake and biomedicine signals.

Parameter optimization based time frequency analysis method for improved generalized S-transform

The present invention discloses a method and a system for noise reduction of a ground penetrating radar B-scan image based on EEMD and permutation entropy. First, a ground penetrating radar two-dimensional B-scan image signal is obtained, and then each obtained B-scan image signal is subjected to noise reduction to obtain the B-scan image signal of the channel after the noise suppression signal, and finally the signal after each channel is recombined to obtain a noise-suppressed two-dimensional B-scan image signal; for any one B-scan image signal, the method for denoising includes: performing EEMD decomposition on the B-scan image signal of the channel to obtain K IMF components arranged from high frequency to low frequency; calculating arrangement entropy values of each IMF component; and selecting an arrangement entropy value not greater than a preset value IMF components to reconstruct, and obtaining the signal after denoising. The invention solves the signal mode aliasing problem existing in the EMD decomposition and can effectively reduce the noise.

Jichao Zhu

Papers

A Noise Suppression Method of Ground Penetrating Radar Based on EEMD and Permutation Entropy

The analysis of ground penetrating radar signal based on generalized S transform with parameters optimization

A Clutter Suppression Method Based on Improved Principal Component Selection Rule for Ground Penetrating Radar

Parameter optimization based time frequency analysis method for improved generalized S-transform

Method and system for noise reduction of ground penetrating radar B-scan image based on EEMD and permutation entropy