Stephen Bocquet

Application of the K+Rayleigh distribution to high grazing angle sea-clutter

The probability distribution of the radar backscatter is commonly used to determine the threshold for separating targets from clutter. Analysis of sea-clutter data collected at high grazing angles, between 15° and 45°, by the Defence Science Technology Organisation (DSTO) Ingara fully polarimetric X-band radar has been used extensively to test distribution models given a large number of samples. The focus of this paper is to determine the most appropriate sea-clutter model for high grazing angle sea-clutter given the smaller number of samples in a typical target detection scenario. For this purpose, a recently proposed K+Rayleigh distribution is introduced to account for the extra Rayleigh scattering observed in the radar backscatter.

Application of the Pareto Plus Noise Distribution to Medium Grazing Angle Sea-Clutter

Robust maritime surveillance with radar requires an accurate description of the backscatter from the sea. The probability distribution of the backscatter is commonly used to determine the threshold for separating targets from clutter. Analysis of data collected at medium grazing angles, between 15° and 45°, by the Defence Science Technology Organisation (DSTO) Ingara fully polarimetric X-band radar has shown that the Pareto distribution is extremely useful as it both captures the high-magnitude components of the sea-clutter and allows significantly simpler optimal and suboptimal detectors to be designed. To further enhance the usefulness of this distribution, this paper presents a multilook formulation which accounts for the thermal noise in the radar. A number of techniques for evaluating the distribution are then presented, including a numerical integration scheme and a number of approximations, which retain the original form of the Pareto distribution.

Simulation of coherent sea clutter with inverse gamma texture

A method for simulating coherent sea clutter has been adapted for Pareto distributed clutter by using an inverse gamma distribution for the local clutter intensity. The model is applied to the range variation of Doppler spectra from Pareto distributed clutter collected at grazing angles of 31°-37° with the DSTO Ingara radar. The model produces Doppler spectra with a Gaussian shape that vary with range in a similar way to those obtained from the data. The simulations contain clutter spikes that replicate the properties of real sea spikes in respect of their intensity statistics, Doppler spectra and position near the wave peaks.

Characterisation of the Ingara HGA dataset

Accurate simulation of sea-clutter is essential to assess the performance of existing target detection schemes and to assist in the development of new ones. A recent simulation technique which captures the evolving Doppler spectrum has been demonstrated in a number of recent publications for both low and high grazing angle data sets. This paper presents empirical models for each of the parameters of this model using the Ingara high grazing angle dataset collected by the Australian Defence Science and Technology Organisation. They are demonstrated through the creation of simulations based on a desired sea-state, collection geometry and polarisation.

Non-coherent Radar Detection Performance in Medium Grazing Angle X-Band Sea Clutter

This paper describes the non-coherent target detection performance of an airborne surface surveillance radar in the presence of medium grazing angle sea clutter. In the absence of frequency agility, the temporal correlation of the sea clutter can be significant and if it is not accounted for in the clutter model, the required signal to interference ratio for a given probability of detection will be incorrect by several decibels, resulting in overestimated performance. This paper describes a robust method for calculating the detection probability for both K and Pareto compound sea-clutter distributions. Empirical models of the amplitude distribution and the speckle correlation are used to determine the expected detection performance given different collection geometries and environmental conditions with the output used to determine the minimum detectable target radar cross section in a detection scenario.