A system may include a mobile ad-hoc network (MANET) including a plurality of nodes. Each of the plurality of nodes is configured to transmit communication data packets and transmit beacons. Each of the plurality of nodes has passive spatial awareness. A first node has information of own node velocity, own node orientation, and a destination. The first node may be configured to: calculate a direct line or an arc from the first node to the destination; utilize passive spatial awareness; assess possible relay routes beyond the communication range and within the beacon range of the first node; determine a next relay node that is on one of the possible relay routes wherein the one of the possible relay routes may be closest to the direct line or the arc without being determined to be part of a dead-end route; and transmit a communication data packet to the next relay node.

A system and method for frequency offset determination in a MANET via Doppler nulling techniques is disclosed. In embodiments, a receiving (Rx) node of the network monitors a transmitting (Tx) node of the network, which scans through a range or set of Doppler nulling angles adjusting its transmitting frequency to resolve Doppler frequency offset at each angle, the Doppler frequency shift resulting from the motion of the Tx node relative to the Rx node. The Rx node detects the net frequency shift at each nulling direction and can thereby determine frequency shift points (FSP) indicative of the relative velocity vector between the Tx and Rx nodes. If the set of Doppler nulling angles is known to it, the Rx node can determine frequency shift profiles based on the FSPs, and derive therefrom the relative velocity and angular direction of motion between the Tx and Rx nodes.

In an example, a method is implemented in a radar system. The method may include transmitting, via transmission channels, a frame of chirps, the chirps transmitted having a programmed frequency offset that is a function of a transmission channel of the transmission channels that is transmitting the frame of chirps, receiving, via a receive channel, a frame of reflected chirps, the reflected chirps comprising the chirps reflected by an object within a field of view of the radar system, and determining a Doppler domain representation of the frame of reflected chirps having a Doppler domain spectrum that includes multiple spectrum bands, the object represented in at least a portion of the spectrum bands based on the reflected chirps, wherein the programmed frequency is configured to cause the Doppler domain spectrum to include a number of spectrum bands greater than the number of transmission channels.

In implementations of systems for estimating three-dimensional trajectories of physical objects, a computing device implements a three-dimensional trajectory system to receive radar data describing millimeter wavelength radio waves directed within a physical environment using beamforming and reflected from physical objects in the physical environment. The three-dimensional trajectory system generates a cloud of three-dimensional points based on the radar, each of the three-dimensional points corresponds to a reflected millimeter wavelength radio wave within a sliding temporal window. The three-dimensional points are grouped into at least one group based on Euclidean distances between the three-dimensional points within the cloud. The three-dimensional trajectory system generates an indication of a three-dimensional trajectory of a physical object corresponding to the at least one group using a Kalman filter to track a position and a velocity a centroid of the at least one group in three-dimensions.

The radio system (10) comprises a waveform generator (1) alternately generating an FMCW wave representing a linearly frequency-modulated continuous wave for radar imaging and a CW wave representing a wave kept at a given frequency for measuring a velocity vector, an amplification chain (2), a set (4) of transmit antennas (41, 42, 43), a set (5) of receive antennas (51, 52, 531, 532), a set (7) of receivers (71-2, 731, 732), and a signal processor (9) implementing processing operations on FMCW signals received from the one or more lateral antennas (51, 52) of the set (5) of receive antennas (51, 52, 531, 532) and spectrally analysing CW signals received from the one or more lateral antennas (51, 52) and from the one or more ventral antennas (531, 532) of the set (5) of receive antennas (51, 52, 531, 532) so as to supply SAR images and components of the velocity vector of said airborne vehicle (20).

A method and structure for solving a Doppler ambiguity problem in a time-division-multiplexed (TDM) frequency modulated continuous wave (FMCW) radar apparatus are proposed. In a frame of a waveform signal transmitted by one transmitting antenna in the TDM FMCW radar apparatus, at least three consecutive chirps having different periods are included for each chirp loop. A Doppler frequency may be determined from phase difference values between the three consecutive chirps measured from an FMCW radar signal received at a receiving antenna. The at least three consecutive chirps having different periods are configured to differ in at least one of an idle time between the chirps or a ramp time of the chirp.

A radar data processing device includes at least one analog-to-digital converter (ADC) configured to digitize a plurality of input signals, wherein each input signal includes radar chirp and radar chirp reflection information received at one of a plurality of receiver antennas. The radar data processing device also includes Fast Fourier Transform (FFT) logic configured to generate FFT output samples based on each digitized input signal, wherein at least some of the generated FFT output samples are across antenna FFT output samples associated with at least two of the plurality of receiver antennas. The radar data processing device also includes a processor configured to determine a plurality of object parameters based on at least some of the generated FFT output samples, wherein the processor uses a neural network classifier trained to provide a confidence metric for at least one of the plurality of object parameters.

Systems and methods for operating radar systems. The methods comprise, by a processor: receiving point cloud information generated by at least one radar device and a spatial description for an object; generating a plurality of point cloud segments by grouping data points of the point cloud information based on the spatial description; arranging the point cloud segments in a temporal order to define a radar tentative track; performing dealiasing operations using the radar tentative track to generate tracker initialization information; and using the tracker initialization information to generate a track for the object.

A system may include a transmitter node and a receiver node. Each node may include a communications interface including at least one antenna element and a controller operatively coupled to the communications interface, the controller including one or more processors. Each node may be time synchronized to apply Doppler corrections to said node's own motions relative to a stationary common inertial reference frame. The stationary common inertial reference frame may be known to the transmitter node and the receiver node prior to the transmitter node transmitting signals to the receiver node and prior to the receiver node receiving the signals from the transmitter node.

Object detection systems and methods are provided. An object detection system comprises a plurality of nodes, each node having a transmitter configured to transmit a radar signal as a beam, and one or more receivers configured to receive a reflected radar signal. The nodes and transmitters are arranged such that the radar beam of one transmitter at least partly overlaps with the radar beam from the transmitter at an adjacent one of the nodes. The object detection system comprises a processor configured to receive a digitised signal from each node, process the digitised signal to detect characteristics of any Doppler effects created by the movement of an object through one or more of the radar beams, compare the Doppler characteristics with Doppler signatures associated with known objects, and thereby classify the object.