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Cognitive frequency diverse array radar with situational awareness

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By jointly utilising the advantages of cognitive radar with situational awareness due to closed‐loop control and frequency diverse array (FDA) with range‐angle‐dependent beampattern, this study proposes a cognitive FDA radar with situational awareness. Different from conventional phased‐array, FDA offers a range‐dependent beampattern. The proposed cognitive FDA radar can avoid undesired strong interferences and focus to the desired targets through the presented closed‐loop control algorithm. This algorithm aims to maximise the receiver output signal‐to‐interference‐plus‐noise ratio (SINR) performance by iteratively optimising the frequency increment in a closed‐loop manner. That is, the cognitive FDA radar can adaptively change its frequency increment according to the environment and thus better performance can be obtained. The cognitive FDA radar performance is evaluated by examining the SINR and direction‐of‐arrival (DOA) estimation mean square errors. How the performance depends on the FDA frequency increment is also investigated. Simulation results show that the cognitive FDA radar yields much better SINR performance and thus higher DOA estimation precision than basic FDA and conventional phased‐array radars.
Institution of Engineering and Technology (IET)
Title: Cognitive frequency diverse array radar with situational awareness
Description:
By jointly utilising the advantages of cognitive radar with situational awareness due to closed‐loop control and frequency diverse array (FDA) with range‐angle‐dependent beampattern, this study proposes a cognitive FDA radar with situational awareness.
Different from conventional phased‐array, FDA offers a range‐dependent beampattern.
The proposed cognitive FDA radar can avoid undesired strong interferences and focus to the desired targets through the presented closed‐loop control algorithm.
This algorithm aims to maximise the receiver output signal‐to‐interference‐plus‐noise ratio (SINR) performance by iteratively optimising the frequency increment in a closed‐loop manner.
That is, the cognitive FDA radar can adaptively change its frequency increment according to the environment and thus better performance can be obtained.
The cognitive FDA radar performance is evaluated by examining the SINR and direction‐of‐arrival (DOA) estimation mean square errors.
How the performance depends on the FDA frequency increment is also investigated.
Simulation results show that the cognitive FDA radar yields much better SINR performance and thus higher DOA estimation precision than basic FDA and conventional phased‐array radars.

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