Knowledge Based Diversity Processing

Abstract

In the past, radar sensing has tended to consist of relatively monolithic, single entity systems that present their output (often in the form of detections on a PPI display) as reports to an operator. The function of the operator is to interpret these reports and subsequently either provide information via a command chain for a decision on how to react, or to make such a decision themselves. In this way the human operator has been the source of intelligence in the sensing system, often aided and abetted by training and experience that has allowed a remarkably wide set of tasks to be performed with a high level of ability. However, the advent of electronic scanning coupled with advances in digital signal processing leads to a class of radar known as ‘Multi-Function’ and these are now challenging traditional methods by placing demands on the radar itself to make well informed, reliable decisions as to how a mission should be conducted. This is leading to the concept of intelligent or cognitive sensing. As a simple example an electronically scanned radar system is able to re-point its beam in timescales that are much faster than human reaction times. Where the beam should next be pointed therefore has to be a decision made by the radar itself. To understand and exploit its environment as fully as possible the system has the option of varying its parameters in a way that is tailored to the information it is seeking. This we term ‘diversity processing’. A logical strategy is to do this in the light of prior experience, its own perception of the world and an appreciation of the task to be carried out. This we term ‘knowledge based processing’. In this chapter we explore the early development of the concept of ‘knowledge based diversity’, drawing upon examples from both synthetic and natural echo locating systems to indicate how, eventually, true intelligence might be incorporated into future sensors.