Real-time wide-field-of-view passive millimeter-wave imaging

Linear Tapered Slot Antennas (TSA) have significant advantages over traditional horn antennas, dielectric rod antenna when used as feed elements in Focal Plane Arrays (FPA) of Passive MilliMeter Wave(PMMW) imaging. In this paper, a novel Antipodal Linear Tapered Slot Antenna(ALTSA) is designed and optimized. The proposed antenna, the gain of which is improved by loading metamaterial structure, is fed by the Substrate Integrated Waveguide(SIW). Simulation and measure analysis show that the good impedance characteristics, low sidelobe levels, high and smooth gain are all achieved in a wide frequency band. Meanwhile, the designed antenna has a smaller aperture width and is easier to form a denser feed array in the focal plane to improve the spatial resolution of passive millimeter wave imaging.

This paper reports development of a passive millimeter wave imaging system for detection of concealed objects using sparse characterization and reconstruction algorithm based on CS theory. By measuring the radiometric temperatures of different objects, passive millimeter wave imaging can acquire images of objects concealed underneath clothing. In this system a millimeter wave antenna controlled by revolving table receives the passive millimeter signal from target object. As passive millimeter wave images have poor contrast and low signal to noise ratio, traditional segmentation algorithms are unable to detect concealed objects, so this system uses a method which transforms the image signal by a non-adaptive base matrix. The high-dimensional signal will be transformed to a lower dimensional space, and then solve an optimization problem for the highest sparsity of the signal through the gradient projection. We present experimental results of 94GHz passive millimeter wave images.

Passive Millimeter Wave Images (PMMWI) can be used to detect and localize objects concealed under clothing. Unfortunately, the quality of the acquired images and the unknown position, shape, and size of the hidden objects render difficult this task. In this paper we propose a method that combines image processing and statistical machine learning techniques to solve this localization/detection problem. The proposed approach is used on an image database containing a broad variety of sizes, types, and localizations of hidden objects. Experiments are presented in terms of the true positive and false positive detection rates. Due to its high performance and low computational cost, the proposed method can be used in real time applications.

Technology advances have made possible the visualization of electron temperature profiles and fluctuations inside the core of high temperature plasmas via a two-dimensional passive millimeter wave imaging system. The electron cyclotron emission imaging (ECEI) system concept and configuration are briefly described. Advanced technologies such as frequency selective surfaces band-stop filter, planar Schottky diode mixer arrays, wide bandwidth IF electronics, and imaging optics are presented.

Passive millimetre wave imaging systems have been developed and their applications investigated at DERA Malvern for several years. In this paper the applications of passive millimetre wave imaging for the detection of exhaust gases is investigated. In principle, this is feasible over the whole of the millimetre wave band. DERA has developed the world's first mechanically scanning real-time passive millimetre wave imager for the Ka band, the lower frequency end of the millimetre wave band. Currently at W-band, DERA is developing a real time imager using MMIC electronics to build the compact focal plane receiver array. Recent developments in MMIC technologies are beginning to make possible development of real time passive millimetre wave imaging systems at the still higher frequencies of the F- and D-bands.

Single-pixel Passive Millimeter Wave (PMMW) imaging system has drawn much attention for its low cost and low complexity. Nowadays, researchers put more effort into the study of the single-pixel PMMW imaging technology as the wide application of Compressive Sensing technology. Previous studies have indicated that the key of the single-pixel imaging technology is the design of coding template. In most studies, a large number of single-templates are applied for coding sampling. These kinds of methods are not suitable for engineering applications due to their low imaging speed. Therefore, a coding method based on quasi cyclic S matrix is proposed, and a novel coding template is designed to improve the imaging speed in this paper. The algorithms of OMP and TVAL3 simulation results in MaTLAB verity the effectiveness of the proposed method.

Passive millimeter wave imaging refers to the passive detection of naturally occurring background millimeter waves. After receiving external millimeter wave thermal radiation signals, the passive millimeter wave detection system will form images based on temperature differences and detect targets. Passive millimeter wave imaging has the advantages of non-radiation, non-contact, perspective imaging, good concealment, small size, and low power consumption. It is widely used in safety inspections, aircraft landing, low visibility navigation, sea surface detection and other fields. Driven by high and new technology, passive millimeter wave imaging low-altitude detection technology is rapidly developing. This paper introduced the basic principle of passive millimeter wave imaging, including the characteristics of millimeter wave radiation and Black-body radiation law, as well as its comparison with ordinary optical radiation. It also described the basic model of current passive millimeter wave imaging low altitude detection technology, explored the shortcomings of this technology and pointed out further work as well.

The purpose of this paper is to propose an algorithm and a novel method for fusion of Passive Millimeter Wave (PMMW) images with their visible images by using Non-subsampled Shearlet Transform (NSST) based on the Spiking Cortical Model (SCM) fusion rule. The parameters of NSST and Improved SCM (ISCM) are selected and optimized based on time consumption and the output of the optimization function like QAB/F. In addition, an effective thresholding method in contourlet transform for PMMW and visible images fusion, which is proposed in our previous paper, is applied to the fusion procedure. Furthermore, NSST is used for analysis of the initial images in different resolutions and directions, followed by using of the ISCM neural network as the fusion rule. Combination of the proposed fusion and thresholding processes resulted in better output images containing visual information close to that of the visible image as well as the hidden object in the millimeter wave image. Moreover, a new evaluation criterion is proposed which does not suffer the shortcomings of the available criteria and improves the previous results for detecting hidden objects by up to 23% with 5% extra time consumption. Finally, the obtained results are evaluated with the available and standard metrics, and all the images exhibited better values than those of the other methods. In fact, the value obtained for the gun image is also acceptable. The results indicate that the proposed fusion method realizes almost all the considered objectives, and the fused image show the objects distinctly in an image with visible details.

The impact of micro and nano technology on millimetre wave imaging from the post war years to the present day is reviewed. In the 1950s whisker contacted diodes in mixers and vacuum tubes were used to realise both radiometers and radars but required considerable skill to realise the performance needed. Development of planar semiconductor devices such as Gunn and Schottky diodes revolutionised mixer performance and provided considerable improvement. The next major breakthrough was high frequency transistors based on gallium arsenide which were initially used at intermediate frequencies but later after further development at millimeter wave frequencies. More recently Monolithic Microwave Integrated circuits(MMICs) offer exceptional performance and the opportunity for innovative design in passive imaging systems. In the future the use of micro and nano technology will continue to drive system performance and we can expect to see integration of antennae, millimetre wave and sub millimetre wave circuits and signal processing.

A novel passive millimeter wave imaging (PMMW) system that utilizes a special arrangement of N equals 36 focal plane elements is presented. N MMW radiometric receivers generate a N X N PMMW image. We discuss the system fabrication and testing.

In this work, we present radiometric images for several concealed object experiments that were measured at TUBITAK — Marmara Research Center (MRC) facilities. The radiometric imaging system that collects the cosmic background radiation from the target is utilized on a 2D data collection grid to have the millimeter-wave image of the target. A detection algorithm is developed to point out the region of the hidden object beneath the cloth. The raw and processed passive millimeter wave images of various targets with concealed objects are shown after applying our detection algorithm. The resultant images have demonstrated that the passive imaging system together with our detection routine produces successful images of the targets.

We describe the development of passive millimeter wave imaging sensors, operating at W band, that are currently being manufactured for commercial markets using standard automated assembly processes. A description of HRL Laboratories' millimeter wave imaging chipset is presented, focusing on parameters that limit sensor performance, such as detector 1/f noise, low noise amplifier noise figure, and gain drift. We conclude with a discussion of ongoing research and development in passive millimeter wave imaging and performance improvements that can be expected for future imaging sensors.

This antenna will be used for PMWIS (passive millimeter wave imaging system) which has 35 GHz operating frequency described as Ka Band. The antenna should work in that specific frequency because of having low attenuation in that region according to frequency behavior in misty conditions. Antenna also should have approximately 50 ohm input impedance value so that perfect matching to the active circuits will occur. The input reflection coefficient, S 11 , has to be under -20 dB and the gain of the antenna, has to be over 10 dB value for better efficiency. Microstrip Vivaldi Fed Antenna provides all of the conditions for imaging system, was designed by using Antenna Magus Computer Program and later it was designed in detail with Computer Simulation Technology Studio Suite Computer Program. The last format of the VFA has -23.1 dB input reflection coefficient, 48.55 ohm input impedance and 12.3 dB gain for 35 GHz OF. It is ready to connect to the LNA and detector, which are active circuits of the PMWIS. At the end, the detector will be connected to the VA and computer. The receiver of PMWIS is composed to the VFA connected to the other equipment that is defined above will scan elevation and azimuth angles, as a result; the VA will transfer the signals to the computer. Computer will show the user the scanning area image. In this system, antenna is the most important section and particular attention was given to the antenna in this study.

Passive imaging systems at millimeter wave (MMW) radio band are in the limelight at the past few years. Passive MMW imaging systems have some essential advantages connecting with high spatial resolution realized at relatively small antenna aperture sizes, secretive mode of operation, lack of operational distance limitations, lack of emitting electromagnetic fields capable cause negative effect on surrounding people and attendant staff. In passive imaging at MMW band one effective method of antenna beam monitoring was invented more then 25 years ago and consisted in scanning antenna realization on the principles of volume-to-surface wave transformation at open electrodynamics systems.

Particle filtering has been proved effective for the state estimation of nonlinear and non-Gaussian systems. To solve the problems of sample degradation and depletion in standard particle filtering tracking algorithm, a novel immune particle filtering target tracking method is proposed in Passive Millimeter Wave (PMMW) imaging. Particle filtering provides a framework in which the posterior density of PMMW target state is represented by a weighted sample set. By using the artificial immune algorithm combined with the Mean Shift algorithm, the samples are optimized during the evolution process. To achieve robust description of the PMMW targets, both gray and gradient orientation distributions are taken into account. Besides, the observation density is established by computing the Bhattacharyya distance between the distribution of the target model and that of the candidate. Experimental results demonstrate that the proposed algorithm is superior to traditional ones when tracking scale changing PMMW targets.