The use of drones for recreational, commercial and military purposes has seen a rapid increase in recent years. The ability of counter-drone detection systems to sense whether a drone is carrying a payload is of strategic importance as this can help determine the potential threat level posed by a detected drone. This paper presents the use of micro-Doppler signatures collected using radar systems operating at three different frequency bands for the classification of carried payload of two different micro-drones performing two different motions. Use of a KNN classifier with six features extracted from micro-Doppler signatures enabled mean payload classification accuracies of 80.95, 72.50 and 86.05%, for data collected at S-band, C-band and W-band, respectively, when the drone type and motion type are unknown. The impact on classification performance of different amounts of situational information is also evaluated in this paper.
This research studies the effects of three noise jamming techniques on the performance of a hybrid multistatic radar network in a selection of different electronic warfare (EW) situations. The performance metrics investigated are the range and velocity estimation errors found using the Cramér-Rao lower bounds (CRLBs). The hybrid multistatic network simulated is comprised of a single active radar transmitter, three illuminators of opportunity (IO), a receiver co-located at the active transmitter site, and two separately located silent receivers. Each IO transmits at a unique frequency band commonly used for civilian applications, including Digital Video Broadcasting-Terrestrial (DVB-T), Digital Audio Broadcasting (DAB), and FM radio. Each receiver is capable of receiving signals at all three IO frequency bands as well as the operating frequency band of the active radar transmitter. The investigations included compare the performance of the network at detecting a single flying target under conditions where different combinations of jammer type, operating mode, directivity, and number of jammers operating are used. The performance degradation of the system compared to operation in a non-contested environment is determined and a comparison between the performance of the hybrid multistatic radar with that achievable by a monostatic radar and an active-only multistatic radar network within a selection of contested scenarios is made. Results show that the use of spatially distributed nodes and frequency diversity within the system enable greater theoretical functionality in the presence of jamming over conventional radar systems.
This work investigates the degradation effects of four distinct jamming signal styles on human micro-Doppler signatures by examining the ability of a linear discriminant classifier to accurately distinguish signatures collected using a simulated frequency modulated continuous wave (FMCW) radar which have been injected with jamming. Misclassification dependence on jamming signal power for each jamming style is presented along with the nature of misclassifications.
This paper presents a quantitative comparison of the detection performance of two multistatic radar detection methods; the first limited by a communications constraint between its constituent nodes and the second with unlimited communications capacity. The methods are tested for a selection of scenarios with differing target positions, and the transmit power requirements to obtain a similar level of detection performance to that of a monostatic radar are analysed. The scenarios simulated are in two-dimensional space and the multistatic system considered is comprised of a single transmit and three distributed receive nodes. A cell-averaging constant false alarm rate is used for the monostatic and both multistatic detection methodologies proposed. It is found that data fusion at a lower level of abstraction, where communications are non-constrained, can lead to better detection performance in multistatic systems. Additionally, the power resource savings compared to an equivalent performance monostatic system are also presented as part of this work.
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