A sound masking system according to the invention is disclosed in which one or more sound masking loudspeaker assemblies are coupled to one or more electronic sound masking signal generators. The loudspeaker assemblies in the system of the invention have a low directivity index and preferably emit an acoustic sound masking signal that has a sound masking spectrum specifically designed to provide superior sound masking in an open plan office. Each of the plurality of loudspeaker assemblies is oriented to provide the acoustic sound masking signal in a direct path into the predetermined area in which masking sound is needed. In addition, the sound masking system of the invention can include a remote control function by which a user can select from a plurality of stored sets of information for providing from a recipient loudspeaker assembly an acoustic sound masking signal having a-selected sound masking spectrum.

Methods and apparatus for detecting, geo-locating and/or classifying a GPS or GNSS jamming signal are disclosed. One such method comprises the steps of analysing a spectrogram of the jamming signal using a tree-based decision process and as a result, then selecting one of a number of types of jamming signal, wherein one of the decisions (1103) in the tree is whether the spectrogram has spectral periodicity.

In order to avoid various jamming attacks from intelligent jammers in modern complex wireless environments, a system and method is presented for a user radio to generate and implement an adaptive anti-jamming communication strategy. The said adaptive anti-jamming communication strategy is obtained via the training process for a specific neural network using Deep Double-Q Reinforcement learning algorithm in the strategy generation phase. The objective of this process is to discover a strategy to select the optimal radio action including transmission channel and transmission power for the user radio, which is changed adaptively to different jamming patterns to maximize the successful transmission rate (“jamming-free”) while retaining the power consumption of user radio as low as possible. In the strategy implementation phase, the user radio chooses an appropriate radio action based on output of trained neural network after the training process; thus, achieves robust and efficient communications against diverse complex jamming scenarios.

The present invention comprises a novel system and method to detect and estimate the time-frequency span of wireless signals present in a wideband RF spectrum. In preferred embodiments, the Faster RCNN deep learning architecture is used to detect the presence of wireless transmitters from the spectrogram images plotted by searching for rectangular shapes of any size, then localize the time and frequency information from the output of the FRCNN deep learning architecture.

The present invention comprises a novel system and method to detect and estimate the time-frequency span of wireless signals present in a wideband RF spectrum. In preferred embodiments, the Faster RCNN deep learning architecture is used to detect the presence of wireless transmitters from the spectrogram images plotted by searching for rectangular shapes of any size, then localize the time and frequency information from the output of the FRCNN deep learning architecture.

Embodiments of communication systems are disclosed for protecting communication between an implanted device ID and an external device ED. Optionally, the ID communicates over the TET channel by modulating a load on the channel. While the ID is communicating the ED optionally adds noise to the TET channel, inhibiting malicious interception of the communication. Using knowledge of the noise signal, the ED cleans the noise from the TET signal to recover the communication from the ID. In some embodiments, the TET link is used to pass an encryption key and/or to verify communications over a radio channel. The TET channel may be authenticated. For example, authentication may include a minimum energy and/or power transfer.

A controller for controlling wireless communication between a node and a master device in a wireless network; wherein the controller comprises a processor arranged for: determining a first directionally restricted jamming area relative to the node; determining a second directionally restricted jamming area relative to the master device; controlling a first directional antenna to transmit a first jamming signal in the first determined directionally restricted jamming area during a predetermined time period; and controlling a second directional antenna to transmit a second jamming signal in the second determined directionally restricted jamming area during the predetermined time period.

According to an embodiment, a communication control device includes a communication unit and a jamming control unit. The communication unit wirelessly communicates with a first device and uploads information acquired from the first device to a second device via a network. The jamming control unit allows jamming radio waves to be output to interfere with wireless communication between the first device and a device other than the communication control device, the device being to perform wireless communication in a communication band used by the first device.

Communication with a key fob of a vehicle can be controlled based on a key fob jamming condition. One or more sensors can be configured to detect the key fob jamming condition. In response to the key fob jamming condition being detected, a jamming device can be activated to cause one or more jamming signals to be emitted. The one or more jamming signals can prevent the key fob from receiving and responding to other signals.

The present disclosure relates to a controller (10) for a counter measure system against unmanned aerial vehicles (UAVs), the controller (10) comprising a display device (18) and a processor configured to: receive target position data indicative of a position of a target UAV; receive effector position data indicative of a position of at least one counter measure effectors (12, 14); receive effector orientation data indicative of an orientation of the at least one counter measure effector (12, 14) relative to geographic cardinal directions; determine a field of effect (30, 32) of the at least one counter measure effector on the basis of the effector position data and the effector orientation data, said field (30, 32) of effect being indicative of an area covered by electromagnetic radiation emitted, in use, by the at least one counter measure effector; and, generate a display signal for displaying, on the display device, the position of the target UAV with respect to the field of effect (30, 32) of the at least one counter measure effector (12, 14).