Abstract: Disclosed is a method of detecting an anomalous propagation condition in a Radar system, comprising the steps of: subtracting returns received in a first receive period from returns received in a succeeding second receive period, and repeating this step for a plurality of receive periods; and if the step of subtracting gives a result in excess of a predetermined threshold in one of the plurality of receive periods, then registering this as a possible anomalous propagation condition.

Abstract: Disclosed is a method of mitigating the effects of anomalous propagation in a Radar system, comprising the steps of: receiving a plurality of returns from a plurality of transmit pulses; calculating a difference in magnitude between each of the plurality of returns and its successor; if one of the calculated differences indicates a first step change greater than a first predetermined threshold, calculating a first average magnitude of the returns received after the first step change, and replacing the returns received before the first step change with synthesised returns having a magnitude equal to the first calculated average magnitude.

Abstract: Disclosed is a method of detecting an anomalous propagation condition in a Radar system, comprising the steps of: subtracting returns received in a first receive period from returns received in a succeeding second receive period, and repeating this step for a plurality of receive periods; and if the step of subtracting gives a result in excess of a predetermined threshold in one of the plurality of receive periods, then registering this as a possible anomalous propagation condition.

Abstract: Disclosed is a method of mitigating the effects of anomalous propagation in a Radar system, comprising the steps of: receiving a plurality of returns from a plurality of transmit pulses; calculating a difference in magnitude between each of the plurality of returns and its successor; if one of the calculated differences indicates a first step change greater than a first predetermined threshold, calculating a first average magnitude of the returns received after the first step change, and replacing the returns received before the first step change with synthesised returns having a magnitude equal to the first calculated average magnitude.

Abstract: There is disclosed a method for counteracting the effect which crags and other such environmental formations can have on radar returns or returns in similar sensor systems. In particular it has been found that the gaps between crags can lead to false detections because of firstly the function of certain signal processors which compare the high frequency return from a certain cell to a low frequency return from that cell, and secondly the effect of smearing of the returns from one cell to another. The invention seeks to mitigate this effect by selecting the maximum low frequency return from a group of range cells as the high frequency offset.

Abstract: There is provided a sensor for use generally within the signal processing unit of a radar system. The sensor enables entity returns to be classified according to the velocity of the entity and thus allows returns to be processed according to classification. In particular, the sensor comprises a first processing means that filters an input signal using a narrow-band notch filter to output a wideband output. In particular, the sensor comprises a second processing means that filters an input signal using a wide-band notch filter to output a narrowband output. The invention provides for the comparison of the outputs to determine how the entity return is to be classified.

Abstract: There is disclosed a method for counteracting the effect which crags and other such environmental formations can have on radar returns or returns in similar sensor systems. In particular it has been found that the gaps between crags can lead to false detections because of firstly the function of certain signal processors which compare the high frequency return from a certain cell to a low frequency return from that cell, and secondly the effect of smearing of the returns from one cell to another. The invention seeks to mitigate this effect by selecting the maximum low frequency return from a group of range cells as the high frequency offset.

Abstract: Described herein is a method of preventing false detections in sensors pulse-Doppler radar mounted on a moving platform. The method comprises filtering each received burst using Doppler filtering to split each received burst into at least a fast channel and one or more slow channels. The slow channel outputs are then used to derive compensation values for the fast channel. In particular, a zero Doppler slow channel is used to derive predicted surface clutter residue information, and a near zero Doppler slow channel is used to derive additional false alarm control attenuation information. Both the predicted surface clutter residue and the false alarm control attenuation information is used to apply compensation to the fast channel and a comparison is done to select the lower of the two values to generate an output signal.

Abstract: There is provided a sensor for use generally within the signal processing unit of a radar system. The sensor enables entity returns to be classified according to the velocity of the entity and thus allows returns to be processed according to classification. In particular the sensor comprises a first processing means that filters an input signal using a narrow-band notch filter to output a wideband output. In particular the sensor comprises a second processing means that filters an input signal using a wide-band notch filter to output a narrowband output. The invention provides for the comparison of the outputs to determine how the entity return is to be classified.

Abstract: Described herein is a method of preventing false detections in sensors pulse-Doppler radar mounted on a moving platform. The method comprises filtering each received burst using Doppler filtering to split each received burst into at least a fast channel and one or more slow channels. The slow channel outputs are then used to derive compensation values for the fast channel. In particular, a zero Doppler slow channel is used to derive predicted surface clutter residue information, and a near zero Doppler slow channel is used to derive additional false alarm control attenuation information. Both the predicted surface clutter residue and the false alarm control attenuation information is used to apply compensation to the fast channel and a comparison is done to select the lower of the two values to generate an output signal.