Browsing by Author "Baker, Chris"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Open Access Development of a passive dual channel receiver at L-band for the detection of drones(IEEE, 2022-06-02) Griffin, Benjamin; Balleri, Alessio; Baker, Chris; Jahangir, Mohammed; Harman, StephenStaring radars use a transmitting static wide-beam antenna and a directive digital array to form multiple simultaneous beams on receive. Because beams are fixed, the radar can employ long integration times to detect slow low-RCS targets, such as drones, which present a challenge to traditional air surveillance radar. The use of multiple spatially separated receivers cooperating with the staring transmitters in a multistatic network allows multi-perspective target acquisitions that can help mitigate interference and ultimately enhance the detection of drones and reduce estimation errors. Here, the development and experimental results of a passive, dual-channel, L-band receiver are presented. The receiver has been used to take measurements of both moving vehicles of drones in flight using a bistatic staring transmitter. An analysis of the receiver is presented using GPS is used to quantify the estimation performance of the receiver.Item Open Access Optimal receiver placement in staring cooperative radar networks for detection of drones(IEEE, 2020-12-04) Griffin, Benjamin; Balleri, Alessio; Baker, Chris; Jahangir, MohammedStaring radars use a transmitting static wide-beam antenna and a directive digital array to form multiple simultaneous beams on receive. Because beams are static, the radar can employ long integration times that facilitate the detection of slow low-RCS targets, such as drones, which present a challenge to traditional air surveillance radar. Typical low altitude trajectories employed by drones often result in low-grazing angle multipath effects which are difficult to mitigate with a monostatic radar alone. The use of multiple spatially separated receivers cooperating with the staring transmitters in a multistatic network allows multi-perspective target acquisitions that can help mitigate multipath and ultimately enhance the detection of drones. This paper investigates how varying the network geometry affects the estimation performance of a targets position and velocity in a multipath free scenario. The optimal geometry is found by minimising the trace of the Cramér-Rao Lower Bound (CRLB) of the Maximum Likelihood (ML) estimates of range and Doppler using the Coordinate Descent (CD) algorithm. The network estimation accuracy performance is verified using Monte Carlo simulations and an ML Estimator on the target parameter estimates.Item Open Access Prototyping a dual-channel receiver for use in a staring cooperative radar network for the detection of drones(IEEE, 2021-07-02) Griffin, Benjamin; Balleri, Alessio; Baker, Chris; Jahangir, MohammedStaring radars use a transmitting static wide-beam antenna and a directive digital array to form multiple simultaneous beams on receive. Because beams are fixed, the radar can employ long integration times to detect slow low-RCS targets, such as drones, which present a challenge to traditional air surveillance radar. The use of multiple spatially separated receivers cooperating with the staring transmitters in a multistatic network allows multi-perspective target acquisitions that can help mitigate interference, such as signal multipath, and ultimately enhance the detection of drones and reduce target parameter estimation errors. Here, the design of a dual-channel receiver prototype for use in a multistatic cooperative network is presented. Several measurements have been taken using the prototype receiver in a bistatic configuration to test and assess its performance.