Ieee transactions on antennas and propagation

An efficient, low-loss, low sidelobe, high dynamic range phased-array radar antenna system is disclosed that uses metamaterials, which are manmade composite materials having a negative index of refraction, to create a biconcave lens architecture (instead of the aforementioned biconvex lens) for focusing the microwaves transmitted by the antenna. Accordingly, the sidelobes of the antenna are reduced. Attenuation across microstrip transmission lines may be reduced by using low loss transmission lines that are suspended above a ground plane a predetermined distance in a way such they are not in contact with a solid substrate. By suspending the microstrip transmission lines in this manner, dielectric signal loss is reduced significantly, thus resulting in a less-attenuated signal at its destination.

Phased array metamaterial antenna system

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Advanced Digital Signal Processing And Noise Reduction

Estimation theory with applications to communications and control

Detection of road boundaries and obstacles is essential for autonomous vehicle navigation. In this paper, we propose a road boundary and obstacle detection method using a downward-looking light detection and ranging sensor. This method extracts line segments from the raw data of the sensor in polar coordinates. After that, the line segments are classified into road and obstacle segments. To enhance the classification performance, the estimated roll and pitch angles of the sensor relative to the scanning road surface in the previous time step are then used. The classified road line segments are applied to track the road boundaries, roll, and pitch angles by using an integrated probabilistic data association filter. The proposed method was evaluated with the autonomous vehicle A1, which was the winner of the 2010 Autonomous Vehicle Competition in Korea organized by the Hyundai-Kia automotive group. The proposed method using the estimated roll and pitch angles can detect road boundaries and roadside, as well as road obstacles under various road conditions, including paved and unpaved roads and intersections.

Enhanced Road Boundary and Obstacle Detection Using a Downward-Looking LIDAR Sensor

The measurements presented in this paper show that feature extraction can be used to identify objects of interest by making use of the scattering present and angular resolution available when using low TeraHertz (low-THz) (0.1 THz-1 THz) devices. The results shown were obtained by measuring two different types of overhead power cables of similar size but with different surface structure which causes the backscatter from each type of cable at 150GHz to be distinct. The measurements are supported by simulations made that incorporate Bragg mode theory.

/pdf/low-thz-overhead-power-cable-signatures-the-effect-of-3nh9pfmm30.pdf

Low-THz overhead power cable signatures: The effect of surface features on Low-THz reflectivities

The potential of the Low THz spectrum for high resolution imaging applications such as automotive radar is described. Outdoor experiments require compact and portable equipment which may be achieved by extending the operation of current battery powered vector network analyzers. The development of radars in the 300 and 670 GHz bands is detailed including instrument performance data and preliminary imaging results.

Compact 300–670 GHz frequency extenders for portable automotive radar applications

The development of automotive remote surface identification system is an important step in ensuring road safety. In this paper we shall discuss a novel approach which addresses the road surface classification process. This method is based on polarimetric radar and sonar data fusion and surface identification using artificial neural network. A modular artificial neural network, which is considered in the paper, allows an overall increase in classification accuracy in the presence of a large number of surface types and a large number of signal features. We shall discuss the techniques involved and present classification results that have been achieved using modular neural network.

/pdf/automotive-surface-identification-system-based-on-modular-3afubdriix.pdf

Automotive surface identification system based on modular neural network architecture

The potential of the Low THz spectrum for high resolution imaging applications such as automotive radar is described. Outdoor experiments require compact and portable equipment which may be achieved by extending the operation of current battery powered vector network analyzers. The development of a hybrid 670 GHz VNA based radar is described including instrument performance data.

A novel 670 GHz hybrid frequency extender for portable automotive radar applications

Sub-terahertz technology (Sub-THz, 200 GHz–700 GHz) is proposed for imaging and recognition of space objects from a space-based sensor, using inverse synthetic aperture radar. Image resolution and quality are achieved thanks to the wide bandwidth available and the enhanced sensitivity of reflected signals in this band to surface texture and small features of the target. An experimental validation in controlled laboratory conditions of the system is presented. Representative parts of real satellites have been measured and images produced at sub-THz frequencies compared to lower frequency images.

Edward Hoare

Papers

Low-THz overhead power cable signatures: The effect of surface features on Low-THz reflectivities

Compact 300–670 GHz frequency extenders for portable automotive radar applications

Automotive surface identification system based on modular neural network architecture

A novel 670 GHz hybrid frequency extender for portable automotive radar applications

Images of satellite elements with a space-borne Sub-THz ISAR system