– Slow fluctuating radar targets have shown to be very difficult to classify using neural networks. This paper deals with the application of time-frequency decompositions for improving the performance of neural networks for this kind of targets. Several aspects, such as dimensionality reduction of the timefrequency representations and the optimum value of SNR for training are discussed. The pro...

In this paper, an analysis of radar range and probability of detection by the use of multiple-input multiple-output (MIMO) radar with cooperative high altitude aeronautical platforms (HAAP) relay (which could operate at stratospheric altitudes) is presented. In this study, a method of cooperative diversity known as ampliy-and-forward (AF) is considered and a target fluctuation model (Swerling I...

In the past decade, object detection has been researched to use a camera, a LIDAR and a RADAR. However, camera-based techniques have heavy image processing and are sensitive for light intensity. LIDAR can measure precise distance from objects, but it is difficult to classify objects. In addition, previous researches were unable to detect partially occluded pedestrian because the data to determi...

Weak signal detection and localization are basic and important problems in radar systems. Radar performance can be improved by increasing the receiver output signal-to-noise ratio (SNR). Localizing the received signal is an important task in the detection of signal in noise. Distorting the localization of the received signal can leads to incorrect target range measurements. In this paper an alg...

The Radar Cross Section of a target plays an important role in the detection of targets by radars‎. ‎This paper presents a new method to predict the bistatic and monostatic RCS of coated electrically large objects. ‎The bodies can be covered by lossy electric and/or magnetic Radar Absorbing Materials (RAMs)‎. ‎These materials can be approximated by the Fresnel reflection coefficients‎. ‎The pro...

In this paper, two suboptimum detectors are proposed for coherent radar signal detection in K-distributed clutter. Assuming certain values for several initial moments of clutter amplitude, the characteristic function of the clutter amplitude is approximated by a limited series. Using the Pade approximation, it is then converted to a rational fraction. Thus, the pdf of the clutter amplitude is o...

This paper presents a systematic scheme for fusing millimeter wave (MMW) radar and a monocular vision sensor for on-road obstacle detection. As a whole, a three-level fusion strategy based on visual attention mechanism and driver's visual consciousness is provided for MMW radar and monocular vision fusion so as to obtain better comprehensive performance. Then an experimental method for radar-vi...

This paper describes the development of the SeaSonde High Frequency Radar system into a dual-use application for the mapping of ocean surface currents and detection of ships at sea. This development entailed the creation of a new radar waveform that would permit this dual-use as well as a detection algorithm to identify the ships in the radar spectra. The detection algorithm utilizes two method...

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the...

Development of the Advanced Multi-Function Array Radar (AMFAR) by APL in the late 1960's represented a new dimension in radar system technology. AMFAR demonstrated the feasibility of automatic detection and tracking with resistance to environmental clutter through computer control. The development of automatic detection and tracking capability in AMFAR eliminated the inherent delays, errors, an...