Speed recognition based on ground vehicle in passive forward scattering radar

The merging of noise reduction and reshaped of the signal in time domain is headed to newfangled clustering methods. After a deep investigation on pre-processing the detection of ground vehicle using passive forward scattering radar (PFSR), principal component analysis (PCA) could be used as spectral signature for target’s speed recognition. The clustering-based PCA able to distinguish the target’s rapidity from the passive forward scattering radar receiver. A small five door hatchback vehicle is used for detection as ground vehicle with several speed and various distance from the passive forward scattering radar receiver. The distance give impact to the clustering-based PCA which is closer vehicle to the passive forward scattering radar offers finer variance of training data in speed recognition

Narrowband elliptic bandpass filter using dual-mode microstrip square loop resonator for WiMax application

In this paper, a narrowband bandpass filter using dual-mode microstrip square loop resonator is proposed. This structure has a 5.1% fractional bandwidth at 2.3GHz. By using some simple techniques, the optimum results will be achieved. The dual-mode resonator will be produced by adding a square patch inside the loop resonator. The simulation and measurement results are also presented. The filter is fabricated on RT/Duroid 6010 substrate having a relative dielectric constant of 10.2 and 0.635 mm thickness. The final dimension is measured at 19.65 mm 19.65 mm. The minimum measured insertion loss is 1.68 dB and return loss obtained is better than -20 dB, where experimental results and simulated values are in good agreement

Low side lobe level multilayer antenna for wireless applications

A low cost and easy fabrication multilayer antenna for wireless applications was presented to cover the industrial, scientific, and medical ISM band of (5.725-5.875) GHz with a gain of 11.7 dB. The antenna was composed of a feeding patch fabricated on a Rogers RT/Duroid 5880 substrate, and three superstrate layers of Rogers RO3006 were located above the feeding patch at a specific height for each layer. The superstrate layers were added to enhance the bandwidth and gain of the antenna and reduce its side-lobe level and return loss. The simulated and measured results of the operating frequency, return loss, bandwidth, and gain for the antenna were presented. CST Microwave Studio was used in this design's simulation

Road pavement density measurements using ground penetrating radar (GPR): simulation analysis

This paper describes a simulation of Ground Penetrating Radar (GPR) nondestructive method at frequency range of 1.7-2.6 GHz to predict density for various road pavement samples. The method used is very simple, fast, contactless and accurate way to determine the density of road pavement. In this work we used frequency range between 1.7-2.6 GHz due to the high penetration in road pavement. The MATLAB software is used to analyze the simulation data and also for the graphs comparisons. An instantaneous method for measuring the density of road pavement was developed by using microwave transmission/reflection technique and free space method at the chosen frequency. The GPR Mixture Model was used to predict the correlation between the attenuation to the parameters related such as effective permittivity, density and thickness

Artificial neural network approach in radar target classification

Problem statement: This study unveils the potential and utilization of Neural Network (NN) in radar applications for target classification. The radar system under test is a special of it kinds and known as Forward Scattering Radar (FSR). In this study the target is a ground vehicle which is represented by typical public road transport. The features from raw radar signal were extracted manually prior to classification process using Neural Network (NN). Features given to the proposed network model are identified through radar theoretical analysis. Multi-Layer Perceptron (MLP) back-propagation neural network trained with three back-propagation algorithm was implemented and analyzed. In NN classifier, the unknown target is sent to the network trained by the known targets to attain the accurate output. Approach: Two types of classifications were analyzed. The first one is to classify the exact type of vehicle, four vehicle types were selected. The second objective is to grouped vehicle into their categories. The proposed NN architecture is compared to the K Nearest Neighbor classifier and the performance is evaluated. Results: Based on the results, the proposed NN provides a higher percentage of successful classification than the KNN classifier. Conclusion/Recommendation: The result presented here show that NN can be effectively employed in radar classification applications

Field test validation of optimized ground penetrating radar (GPR) mixture model at frequency range 1.7 GHz to 2.6 GHz

This paper presents the validation of optimized GPR mixture model based on the microwave nondestructive free space method in order to determine the density of road pavement. Density is an important parameter to determine the compressive strength of road pavement for road user safety. The attenuation is a major factor for gathering the density of road pavement predictly. A few of measured attenuation were taken at nine road pavement slab samples in laboratory. The GPR mixture model has been used to produce the simulation data to predict the attenuation. The comparison results between measurement and simulation were investigated. The best performance of GPR mixture model was selected in the optimization technique due to the smallest mean error. An improved attenuation formula or optimized GPR model was obtained from the optimization technique. The validation at field test had been conducted in order to see the performance of optimized GPR model

Speed Recognition Based on Ground Vehicle in Passive Forward Scattering Radar

The merging of noise reduction and reshaped of the signal in time domain is headed to newfangled clustering methods. After a deep investigation on pre-processing the detection of ground vehicle using passive forward scattering radar (PFSR), principal component analysis (PCA) could be used as spectral signature for target’s speed recognition. The clustering-based PCA able to distinguish the target’s rapidity from the passive forward scattering radar receiver. A small five door hatchback vehicle is used for detection as ground vehicle with several speed and various distance from the passive forward scattering radar receiver. The distance give impact to the clustering-based PCA which is closer vehicle to the passive forward scattering radar offers finer variance of training data in speed recognition

A ground based circular synthetic aperture radar

Detecting on-the-ground objects is a subject of interest for some applications. Typical example is foreign object detection on the airport runway. In response to this demand, a ground-based Circular Synthetic Aperture Radar (CSAR) system is proposed and explained in the paper. In the proposed CSAR, the antennas represent a circular movement trajectory. Wideband Linear Frequency (LFM) chirps were used for transmission. A simulation model for CSAR, based on the Doppler Effect between the radar and object is developed in this paper. In addition, a processing method for object detection using correlation between image data produced by simulation and experimental data is developed. The resultant of the simulated model at each point, which represents the object's behavior in an ideal and clutter-free environment, is used as a template for object detection. Simulation and experimental results demonstrate that the proposed method is well suited in detecting small objects at different positions

RCS classification on ground moving target using LTE passive bistatic radar

Detection and location on the ground moving target are a function of dependent bistatic Radar Cross Section (RCS) and radar design parameters which in this experimental study used LTE signal as a source for passive bistatic radar (PBR). Ground moving target also can be classified in dimensions using conventional processing approaches which we performed a simulation using Computer Simulation Technology (CST) Microwave studio. The target bistatic radar cross-section will give a realistic calculation on PBR performance with the requirement of complete treatment. Three models of ground moving target are designed using Autodesk software which the models are classified as compact car, saloon car and sport utility vehicle (SUV) for size of small and medium and large respectively. The designs are for observation on the performance of RCS using a bistatic area between transmitter and receiver with the frequency transmit signal from long-term evolution (LTE) based station is 2.6 GHz and with far-field conditions. The simulation results show that largest area of ground moving target, SUV had better outcome compared to other ground moving target which reliable with Babinet’s principle, which declares a target of physical cross-sectional area is proportionate to RCS. Different cross-sectional area of transmitting signal from other ground moving target give smaller RCS which cause from the reduction area of reflected signal such as compact car according to small size and saloon car according to medium size. This might improve the sensitivity of LTE passive bistatic radar if using greater size of ground moving target for a better RCS performance

A Linear Frequency Modulated bistatic radar for on-the-ground object detection

A radar system for detecting and localizing small targets on the ground is proposed in this paper. The system transmits wideband Linear Frequency Modulated pulses from ground-based transmitter. The reflected pulses will be collected simultaneously by two different ground-based receivers installed in different bistatic positions. Accurate range processing in this bistatic configuration will lead us to detect small objects like N-type connectors in several meters distances