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.
In this paper the development of a hybrid active and passive experimental radar system utilising a low-cost Software Defined Radio is explored. The potential future evolution from monostatic to multistatic sensing is described and the synchronisation performance limitations of the system are summarised through a number of preliminary laboratory experiments. In addition, the first of a series of practical radar experiments are presented in order to verify the systems active and passive sensing modes.
In this paper the topic of joint active and passive (hybrid) radar detection is introduced and the theoretical benefits are outlined. An experimental hybrid radar setup is presented where a low-cost Software Defined Radio (SDR) based radar system is used for hybrid sensing of targets using active and Passive Bistatic Radar (PBR). Experimental results are presented for simultaneously sensing using an active 2.4 GHz radar and 690 MHz Digital Video Broadcasting -Terrestrial (DVB-T) based PBR mode. The detection performance of each sensor and a joint sensor performance are evaluated, where the joint detection performance is found to exceed that of the individual sensors alone. The ability to reduce active radar transmissions, but still retain a reasonable detection performance, is investigated using experimental data and the case is made for adaptive behaviour in order to exploit the benefits available to hybrid radars.
Radio Frequency (RF) sensors are often designed to operate in a single mode or configuration. Demands coming from operating in future challenging Electromagnetic Environment (EM) conditions require innovative solutions and significant changes from current radar architectures. This paper provides a system level review of a modular multi-function RF sensor solution which allows for a N node solution which can be either used to drive a singular powerful array solution OR deployed as N multistatic RF sensor nodes. Both solutions use a common digital solution which is based on the Xilinx Radio Frequency System on a Chip (RFSoC) technology. An antenna array operating at C-band has been designed for the project, along with daughter-boards which facilitate access to all 8 receive channels from the Xilinx ZCU111 RFSoC development board. A solution to the challenges of synchronising the ADC channels (including across multiple ZCU111 boards) is also presented, with results showing the synchronisation performance.
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