A Cognitive Approach for Transmit Waveform Generation for Active Phased Array Multifunction Radars

Multifunction radar utilizes a wide combination of frequencies, pulse lengths, modulations and many other programmable parameters among other factors to cater for different functions of the radar. Conventionally radar waveforms are predefined as per mode of operation. In Cognitive approach, radars pick up waveforms in real time in accordance with the conditions of operation such as to minimize spectral interference or track a target with sufficient resolution or counter jamming etc. The combinations of waveform parameters are adapted cognitively in every dwell or pulse to pulse within a dwell on this basis. This work presents a digital implementation of waveform generation module designed to adapt to the environment in real time and digitally generate the appropriate waveform for transmission in multi-function radars. For a radar to be cognitive it is of umpteen importance that in real time it learns from the environment and utilizes the information to intelligently adjust the transmit waveform parameters. The design presented here leverages data and real-time statistics obtained through feedback from the receiver to transmitter. This feedback mechanism enables intelligent operation in the radar system. Thus, this work is an attempt towards building a module for transmit waveform generation in radars that learns and optimizes design parameters such as resolution, pulse width, bandwidth, and modulation cognitively on the fly. It also incorporates platform motion compensation for radars on moving platform and anti-jamming measures in real time as per operational conditions.

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Published
2024-12-01
DOI
https://doi.org/10.1109/tencon61640.2024.10902888
Primary Topic
Radar Systems and Signal Processing
Type
article
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article

A Cognitive Approach for Transmit Waveform Generation for Active Phased Array Multifunction Radars

Taniza Roy
Radar Systems and Signal Processing
article

A Cognitive Approach for Transmit Waveform Generation for Active Phased Array Multifunction Radars

Taniza Roy
article en

Abstract

Multifunction radar utilizes a wide combination of frequencies, pulse lengths, modulations and many other programmable parameters among other factors to cater for different functions of the radar. Conventionally radar waveforms are predefined as per mode of operation. In Cognitive approach, radars pick up waveforms in real time in accordance with the conditions of operation such as to minimize spectral interference or track a target with sufficient resolution or counter jamming etc. The combinations of waveform parameters are adapted cognitively in every dwell or pulse to pulse within a dwell on this basis. This work presents a digital implementation of waveform generation module designed to adapt to the environment in real time and digitally generate the appropriate waveform for transmission in multi-function radars. For a radar to be cognitive it is of umpteen importance that in real time it learns from the environment and utilizes the information to intelligently adjust the transmit waveform parameters. The design presented here leverages data and real-time statistics obtained through feedback from the receiver to transmitter. This feedback mechanism enables intelligent operation in the radar system. Thus, this work is an attempt towards building a module for transmit waveform generation in radars that learns and optimizes design parameters such as resolution, pulse width, bandwidth, and modulation cognitively on the fly. It also incorporates platform motion compensation for radars on moving platform and anti-jamming measures in real time as per operational conditions.

Defence Research and Development Organisation (IN)
Affordable and clean energy
Openalex Percentile: Top 53%
Radar Systems and Signal Processing
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