A computer-implemented method is provided for identifying a target amid clutter and minimize cross-talk from receive signals returned therefrom via a Multiple Input Multiple Output (MIMO) radar system that emits transmit signals into a resolution cell that contains the target and the clutter. The method includes employing a match filter to estimate a set of parameters from each receive signal of the receive signals; determining interference correlation; estimating clutter correlation; forming an optimum detector with the estimated correlation for each receive signal among the receive signals; employing the optimum detector to estimate the target set of parameters from each receive signal as an estimated target parameter; returning to the forming operation in response to the estimated target parameter exceeding an established tolerance; and applying the estimated target parameter to the receive signals for submission to the MIMO radar system.

An airborne radar system and signal interpretation approach that detects slow moving ground targets using angle and Doppler of Keystone formatting process, and is referred to as Angle-Doppler Keystone Formatting (ADK). ADK collapses the clutter ridge to a constant Doppler or to a constant angle, thereby transforming a clutter ridge in angle-Doppler space into a horizontal line of constant Doppler or a vertical line of constant angle. Clutter may then be filtered more effectively, such as by using multiple beams as the source of STAP training data or by using multiple Doppler bins.

Techniques are described herein for allowing one or more vehicles or radar systems in an environment to passively detect radar signals from other vehicles or other radar systems and determine spatial parameters of objects based on the passively received radar signals. A primary vehicle (or user equipment (UE) associated with the primary vehicle) may be configured to receive one or more radar signals from one or more secondary vehicles (or UEs associated with the secondary vehicles). The primary vehicle may be configured to determine one or more spatial parameters of the secondary vehicle based on the passively received radar signals. In some cases, the primary vehicle may receive an indication that identifies at least some communication resources to be used by the secondary vehicle to transmit the radar signals. The primary vehicle may determine one or more driving operations based on determining the spatial parameter.

A method for creating a virtual reception channel in a radar system includes an antenna possessing two physical reception channels (1.sub.r, 2.sub.r) spaced apart by a distance d in a direction x, two emission channels (1.sub.e, 2.sub.e) spaced apart by the same distance d in the same direction x and processing means, the method comprising: dynamically selecting two different waveforms, the waveforms being orthogonal to each other; generating a radar pulse of given central wavelength in each emission channel, each of the emission channels emitting one of the two different waveforms; acquiring with the reception channels echoes due to pulses emitted by the emission channels and reflected by at least one target; compressing the pulses by matched filtering of the echoes acquired by each physical reception channel, this involving correlating them with each of the waveforms generated in the emission channel; and repeating steps a) to c) while randomly changing one of the values of each of the phase codes associated with the generated waveforms until the level of the sidelobes of all the compressed pulses has stabilized; and radar system for implementing such a method.

Integrated circuits may include a constant false alarm rate (CFAR) detection circuit, which may identify targets among clutter and noise in a range-Doppler map. The CFAR detection circuit may compute power values for each cell in the range-Doppler map and scan the range-Doppler map cell by cell. For this purpose, the CFAR detection circuit may compute a target value for a cell-under-test and surrounding cells and a noise value for one or more regions in local proximity of the cell-under-test on the range-Doppler map. For example, the CFAR detection circuit may perform a two-dimensional filtering to compute the target value and compute a sum of accumulated power values weighted by predetermined coefficients. The predetermined coefficients may taper at edges of the range-Doppler map and/or at edges of the regions. The CFAR detection circuit may declare a target based on a comparison of the target value and noise value.

The present invention suggests a target detecting apparatus and method using a radar which detect a target using a recursive modified cell average-constant false alarm rate (RMCA-CFAR) detector without having a sorting process. The present invention provides a target detecting apparatus using a radar, the apparatus including: a data selecting unit which compares reference data with at least one of previous data and subsequent data which are located at both sides of the reference data, from a received signal including information on a distance and a speed for multiple targets, to select specific data; a cell average calculating unit which calculates an average of cells extracted using a sliding window including the specific data; a CFAR data detecting unit which detects CFAR data based on the average of the extracted cells; and a target detecting unit which detects the target based on the CFAR data.

A system and method characterizes the height of targets in an environment around a vehicle. Signals are transmitted into the environment and return signals are received to determine a track corresponding to a target. For each track, bins are generated, each bin corresponding to a segment of the range, the segments having a gradually increasing size between the minimum range and maximum range. Range and magnitude values of the received return signals are determined for a selected track. A plurality of filled bins are determined, filled bins indicating that a return signal within the selected track has a range value falling within the segment corresponding to said bin. When the number of filled bins exceeds a set threshold, the return signals having range values within the segments corresponding to the filled bins are analyzed to characterize a height of the target.

Disclosed is a method of mitigating the effects of anomalous propagation in a Radar system, comprising the steps of: receiving a plurality of returns from a plurality of transmit pulses; calculating a difference in magnitude between each of the plurality of returns and its successor; if one of the calculated differences indicates a first step change greater than a first predetermined threshold, calculating a first average magnitude of the returns received after the first step change, and replacing the returns received before the first step change with synthesised returns having a magnitude equal to the first calculated average magnitude.

An adaptive finite impulse response (FIR) filter for filtering an I/Q data stream having a sample period. The FIR filter comprises at least one sample-period tap delay configured to delay the I/Q data stream by an integer multiple of the sample period of the I/Q data stream, and at least one sub-sample-period tap delay configured to delay the I/Q data stream by a non-integer multiple of the sample period of the I/Q data stream. A set of adaptive weights is provided and configured to weight samples of the delayed I/Q data stream. An adder is responsive to the weighted samples and configured to combine the weighted samples of the delayed I/Q data streams to generate a filtered I/Q data stream.

A phase Doppler radar system may comprise a pulse Doppler receiver/transmitter (R/T) subsystem coupled with a processing subsystem. The system may determine target velocity and target detection events by collecting pulses from the pulse Doppler R/T subsystem, determine an undifferentiated phase of each of the pulses, differentiate the pulses, and determine a differentiated phase of each of the pulses. The system may perform a linear fit of the differentiated phases of the pulses to produce a slope and an intercept. The system may determine a set of initial estimates of coefficients of a nonlinear fit equation. The system may perform iterations of a nonlinear least squares fit, beginning with the initial coefficient estimates, to produce a non-linear fit result. The system may determine a goodness-of-fit (GoF) statistic associated with the nonlinear fit result, and declare a detection event when the GoF is superior to a GoF statistic associated Gaussian noise.