Correlated Non-Coherent Radar Detection for Gamma-Fluctuating Targets in Compound Clutter

This work studies the problem of radar detection of correlated gamma-fluctuating targets in the presence of clutter described by compound models with correlated speckle. If the correlation is not accounted for in a radar model, the required signal-to-interference ratio for a given probability of detection will be incorrect, resulting in over-estimated performance. Although more generally applicable, the is focus on airborne maritime radar systems. Hence K-distributed sea clutter is used as the main example. Detection via square-law non-coherent pulse integration is formulated in a way that accommodates arbitrary partial correlation for both target radar cross-section (RCS) and clutter speckle. The obstacle to including this degree of generality in previous work was the fact that Swerling's original characterization of the standard RCS fluctuation classes as gamma distributions for the power is not sufficient for the inclusion of both correlation sources (i.e.target and clutter speckle) for gamma-fluctuating targets. An extension of the model is required at the quadrature component (i.e. voltage) level, as phase relationships can no longer be neglected. This is addressed in the present work, which not only postulates an extended model, but also demonstrates how to efficiently compute it, with and without a number of simplifying approximation schemes within the framework of the saddle-point technique.

Correlated Non-Coherent Radar Detection for Gamma-Fluctuating Targets in Compound Clutter

This work studies the problem of radar detection of correlated gamma-fluctuating targets in the presence of clutter described by compound models with correlated speckle. If the correlation is not accounted for in a radar model, the required signal-to-interference ratio for a given probability of detection will be incorrect, resulting in over-estimated performance. Although more generally applicable, the is focus on airborne maritime radar systems. Hence K-distributed sea clutter is used as the main example. Detection via square-law non-coherent pulse integration is formulated in a way that accommodates arbitrary partial correlation for both target radar cross-section (RCS) and clutter speckle. The obstacle to including this degree of generality in previous work was the fact that Swerling's original characterization of the standard RCS fluctuation classes as gamma distributions for the power is not sufficient for the inclusion of both correlation sources (i.e.target and clutter speckle) for gamma-fluctuating targets. An extension of the model is required at the quadrature component (i.e. voltage) level, as phase relationships can no longer be neglected. This is addressed in the present work, which not only postulates an extended model, but also demonstrates how to efficiently compute it, with and without a number of simplifying approximation schemes within the framework of the saddle-point technique.

Observation of quadrocopters by radar with long-term coherent signal accumulation

The article discusses the experimentally obtained characteristics of radar signals reflected from small-sized aerial targets such as a quadrocopter, with their long-term coherent accumulation. A brief description of the structural diagram of the experimental radar and its characteristics is given. The radar operates in the ten-centimeter wavelength range and emits a coherent-pulse signal. The duration of the emitted chirp pulse is 1 μs with a compression ratio of 15. Algorithms for primary processing of signals in a computer are given, including compression of chirp signals and spectral analysis of the received implementation, which is equivalent to its coherent accumulation. The parameters of the generated radar image are determined. The characteristics of the targets used - the small-sized quadcopters Mavic and Phoenix – are given. As a result of the experiments, it was shown that the tested small-sized air targets in the ten-centimeter wavelength range of the probing signal have their own coherence time sufficient for the coherent accumulation of the signal reflected from them for a time of at least 0.2 seconds. The Mavic does not produce reflections from its rotating rotors. The main rotor of the Phoenix quadcopter creates spectral components in the image, concentrated along the speed axis in the form of maxima symmetrically located relative to the central mark of the target. The presence of this feature of the signal allows you to identify the type of target, highlight the target against the background of birds, and detect a stationary, hovering target. It is shown that the features of signals reflected from the ground, with long-term coherent accumulation, allow providing the minimum speed of the detected target, measured in fractions of a meter per second.