A traffic radar system comprises a first radar transceiver assembly, a second radar transceiver assembly, a display, and a processing element. The first radar transceiver assembly transmits and receives radar beams and generates a first electronic signal corresponding to the received radar beam. The second radar transceiver assembly transmits and receives radar beams and generates a second electronic signal corresponding to the received radar beam. The display displays a plurality of speeds, each speed being a speed of a target vehicle. The processing element is configured to receive the first and second electronic signals, process the first electronic signal to determine speeds of target vehicles in the front zone, process the second electronic signal to determine speeds of target vehicles in the rear zone, and control the display to display the speeds of target vehicles in the front zone or target vehicles in the rear zone based on predetermined parameters.

A traffic radar system comprises a first radar transceiver assembly, a second radar transceiver assembly, a display, and a processing element. The first radar transceiver assembly transmits and receives radar beams and generates a first electronic signal corresponding to the received radar beam. The second radar transceiver assembly transmits and receives radar beams and generates a second electronic signal corresponding to the received radar beam. The display displays a plurality of speeds, each speed being a speed of a target vehicle. The processing element is configured to receive the first and second electronic signals, process the first electronic signal to determine speeds of target vehicles in the front zone, process the second electronic signal to determine speeds of target vehicles in the rear zone, and control the display to display the speeds of target vehicles in the front zone or target vehicles in the rear zone based on predetermined parameters.

Systems and methods for training and using machine learning models to classify vehicles from highway radar systems are provided. The training systems may use auxiliary radar processing to separate events by lane, length, and/or speed, and then use separate event data groups pooled from similar or proximate lanes, lengths, and/or speeds to train multiple models. At estimation time, incoming events may be grouped using similar groupings as those used during training to select which model to use. An incoming event may be applied to the neural network operations of the selected model to generate an estimate. Generating an estimate may involve successive applications of multiple linear convolutions and other steps along varying or alternating dimensions of the in-process data.

A system determines absolute speed of a moving object. In AM, time of flight data over a time period is processed to determine ranges between the system and the moving object. The system performs linear regression analysis on the collected ranges to calculate the radial velocity. The system measures angular swivel rate of the system to determine tangential velocity. From the radial velocity and tangential velocity, the absolute speed can be calculated by taking the square root of the addition of the square of the radial velocity and square of the tangential velocity. In MM, the system calculates object distance, i.e. distance in the direction of travel, by subtracting the square of a pre-determined perpendicular distance L, perpendicular to the direction of travel, from a square of line-of-sight distance R, and taking square root of the result. Absolute speed is determined by calculating the slope of modified linear regression curve-fit.

In accordance with described examples, a method determines if a velocity of an object detected by a radar is greater than a maximum velocity by receiving on a plurality of receivers at least one frame of chirps transmitted by at least two transmitters and reflected off of the object. A velocity induced phase shift (.sub.d) in a virtual array vector S of signals received by each receiver corresponding to a sequence of chirps (frame) transmitted by each transmitter is estimated. Phases of each element of virtual array vector S are corrected using .sub.d to generate a corrected virtual array vector S.sub.c. A first Fourier transform is performed on the corrected virtual array vector S.sub.c to generate a corrected virtual array spectrum to detect a signature that indicates that the object has an absolute velocity greater than a maximum velocity.

In accordance with described examples, a method determines if a velocity of an object detected by a radar is greater than a maximum velocity by receiving on a plurality of receivers at least one frame of chirps transmitted by at least two transmitters and reflected off of the object. A velocity induced phase shift (.sub.d) in a virtual array vector S of signals received by each receiver corresponding to a sequence of chirps (frame) transmitted by each transmitter is estimated. Phases of each element of virtual array vector S are corrected using .sub.d to generate a corrected virtual array vector S.sub.c. A first Fourier transform is performed on the corrected virtual array vector S.sub.c to generate a corrected virtual array spectrum to detect a signature that indicates that the object has an absolute velocity greater than a maximum velocity.

A method for measuring, using a radar or sonar, the velocity with respect to the ground of a carrier moving parallel to the ground, includes the following steps: a) orienting the line of sight of the radar or sonar toward the ground; b) emitting a plurality of radar or sonar signals (P.sub.1-P.sub.N) that are directed toward the ground, and acquiring respective echo signals (E.sub.1-E.sub.N); c) processing the acquired echo signals so as to obtain, for one or more echo delay values, a corresponding Doppler spectrum; d) for the or at least one the echo delay value, determining a high cut-off frequency of the corresponding Doppler spectrum; and e) computing the velocity of the carrier with respect to the ground on the basis of the one or more high cut-off frequencies. A system allowing such a method to be implemented.

The present invention relates to a system and method for the monitoring and surveillance of one or more vehicles (120) moving on one or more roadways (300) and to the detection and recording of images and/or videos of speeding infractions by vehicles (120) moving on the roadway (300). The invention also relates to an unmanned air vehicle (10) that carries out the method according to the invention together with a base station (80), with which it forms the system according to the invention.

The present invention relates to a system and method for the monitoring and surveillance of one or more vehicles (120) moving on one or more roadways (300) and to the detection and recording of images and/or videos of speeding infractions by vehicles (120) moving on the roadway (300). The invention also relates to an unmanned air vehicle (10) that carries out the method according to the invention together with a base station (80), with which it forms the system according to the invention.

In accordance with described examples, a method determines if a velocity of an object detected by a radar is greater than a maximum velocity by receiving on a plurality of receivers at least one frame of chirps transmitted by at least two transmitters and reflected off of the object. A velocity induced phase shift (.sub.d) in a virtual array vector S of signals received by each receiver corresponding to a sequence of chirps (frame) transmitted by each transmitter is estimated. Phases of each element of virtual array vector S are corrected using .sub.d to generate a corrected virtual array vector S.sub.c. A first Fourier transform is performed on the corrected virtual array vector S.sub.c to generate a corrected virtual array spectrum to detect a signature that indicates that the object has an absolute velocity greater than a maximum velocity.