Defence Research Agency

About: Defence Research Agency is a based out in . It is known for research contribution in the topics: Synthetic aperture radar & Radar. The organization has 1211 authors who have published 1109 publications receiving 31542 citations.

Comments on "Statistical and spatial properties of forest clutter measured with polarimetric synthetic aperture radar

Abstract: For original paper see ibid., vol.30, no.3, p.578-88 (1992). Sheen and Johnston have derived a theoretical expression for the intensity autocorrelation function of a synthetic aperture radar (SAR) image based on the product model for SAR clutter. This derivation is valid under the assumption that the instrument function width is narrow relative to the width of the texture autocorrelation function. This communication draws attention to a more general derivation of the intensity autocorrelation function, given by Oliver, which does not require this assumption. >

Enhancement of coherent laser radar performance by predetection amplification.

Abstract: A long-path carbon dioxide laser amplifier, based on a coaxial radio frequency discharge gain medium combined with a Herriott cell folding system, is investigated as a predetection amplifier in a coherent laser radar system. The amplifier signal gain and noise characteristics are measured, and the signal-to-noise enhancement produced in a Doppler radar system is determined over a range of operating conditions of the amplifier. A maximum enhancement factor of 12.4 dB is measured for a cw gain cell, which is in good agreement with the theoretical prediction.

Design of a real-time high-quality SAR processor

Abstract: Research at the DRA, Malvern, has resulted in a series of algorithms which are capable of yielding focused, undistorted SAR imagery. Unfortunately these can only be implemented in a fraction of a percent of real-time on a standard work-station. In parallel with the algorithm development, therefore, has been research into a real-time implementation on a parallel computer (the Meiko CS1). This paper outlines the principles behind the software architecture design to achieve the desired speed. Processing functions considered include: initial motion compensation (based on accelerometer data), autofocus with phase correction, final processing and an intensity segmentation stage. Real time processing rates of about 10 MBytes/s are now routinely achieved. We indicate the compromises between processor power, available local memory and communications bandwidth needed to achieve real-time operation. Detailed timings derived from the implementation will be presented together with a discussion of the manner in which this could be varied for different SAR configurations. In parallel with the work on producing real-time high quality imagery has gone a program of research into automated image-understanding techniques. This work is now reaching the stage where reliable algorithms for several basic operations, including segmentation and change detections, exist in a form capable of processing continuous imagery at real time or near real-time rates. Provision has been made for the inclusion of these algorithms as postprocessing stages in the real-time SAR processor.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Simultaneous segmentation of texture properties of K-distributed SAR images

Abstract: This paper proposes a technique for refining a previous segmentation by using different properties of K-distributed SAR clutter simultaneously. We first consider approximate forms for the K distribution based on a Maximum Entropy approach which assumes that only two moments of the data can be estimated with sufficient accuracy over a small sample region. The choice of moments defines the form of the approximate probability density functions (PDF). After the initial segmentation we then propose a post-processing stage in which the values of the moments of the complete previously-identified segments are assumed exact and an optimum fit to the edge position is defined. We demonstrate that joint estimation of the edge position, based on estimates of the mean of the data and of its logarithm, provides a close approximation to the full K- distribution treatment, while being significantly simpler to implement.

Comparison of the performance of vector quantiser training algorithms

Abstract: The vector quantiser (VQ) is a single layer winner-takes-all neural network. The 'transformation' performed by the VQ consists of two components, an encoding operation and a code book that stores the allowed codes and the vectors that correspond to them, known as code vectors. The VQ can also be used to perform lossy data compression, but it is not robust to corruption of the code indices. The Kohonen self-organising map is a close relative of the VQ, and would appear to be a good candidate to provide encodings that are robust to channel noise, because of the topological ordering of the code vectors. However Luttrell has shown that a kind of VQ, known as the topographic VQ (TVQ) emerges naturally when considering a single VQ transmitting codes along a noisy communications channel. The theory regarding the training and encoding TVQ is reviewed within the context of a noisy communications channel. Simulations are presented showing that TVQ's are more robust to noise than the Kohonen map. Lastly, it is shown that the TVQ has the same code vector density as the VQ.