Implementations disclosed describe techniques and systems for efficient estimation of spatial characteristics of an outside environment of a wireless device. The disclosed techniques include generating multiple covariance matrices (CMs) representative of obtained sensing values. Different CMs may be associated with different frequency increments used in sensing signals to probe the outside environment. The disclosed techniques may further include determining eigenvectors for the CMs, and identifying, based on the determined eigenvectors, one or more spatial characteristics of the object in the outside environment.

A method is provided which includes transmitting a first radar frame over a first communication channel and transmitting a second radar frame over a second communication channel. A reflection of the first radar frame is received, and a first channel impulse response is estimated based on a reflection of the first radar frame. A reflection of the second radar frame is received, and a second channel impulse response is estimated based on a reflection of the second radar frame. The first channel impulse response estimate and the second channel impulse response estimate are combined to obtain a channel impulse response estimate having a higher resolution than each of the first channel impulse response estimate and second channel impulse response estimate.

A method for the model-based, high-resolution separation of radar targets for a radar sensor, in which the radar sensor initially generates radar data by capturing radar targets by sampling a field of view of the radar sensor. Various model orders are calculated for the number of radar targets with the aid of a grid-based method and are interleaved in one another. A highest model order is specified, and only the highest model order is calculated, so that the lower model calculations are implicitly produced from the calculation of the highest model order.

A method for a radar system is presented, for detecting the surroundings using transmission means for emitting transmission signals which contain a sequence of at least approximately identical individual signals, the sequence of individual transmission signals being repeated cyclically, said method being characterized in that over the sequence of the individual signals the frequency position thereofoptionally apart from a varying and at least approximately mean value-free componentis changed at least approximately linearly and, in the process, the slope of the linear frequency position change over the individual transmission signals is at least sometimes varied from sequence to sequence, in particular in order to increase the radial distance and/or relative speed measurement accuracy and/or in order to be more robust in respect of interference with other radar systems.

Conventional ESPRIT (Estimation of Signal Parameters via Rational Invariance Techniques) cannot be directly applied to SFCW MIMO radar for localization of targets as the performance would be restricted by geometry of spatial MIMO. Thus, the present disclosure provides a method and system for localization of targets using SFCW MIMO radar. In this method, the channel response of the virtual uniform rectangular array (vURA) obtained by scanning at uniformly spaced frequency points is combined to form a larger array referred as Space-Frequency (SF) array. The 3D localization of targets is done by estimating azimuth angle, elevation angle and range using this SF array. The localization capability of the disclosed method largely depends upon the number of frequency scanning points and enables localizing far more targets than the dimension of the vURA. In addition, the inter-element spacing requirement of vURA is also greatly relaxed.

A radar device is disclosed. The radar device includes a transmitting unit that radiates a transmission pulse, and a receiving unit that receives an echo pulse reflected from a target object. The receiving unit includes a multi-receiving circuit AFE including a plurality of receiving circuits that amplifies an echo pulse to output an amplified signal and an analog signal summing circuit that generates a summed signal, a sampling circuit that repeatedly performs a sampling operation on the summed signal to generate a plurality of sampling data, a signal integrator that generates integrated data for each of range cells, a statistical signal converter that acquires noise statistical data and generates an extracted signal, and an AFE controller that performs a characteristic verification operation for the noise statistical data and adjusts the summed signal.

The present invention relates a method of improving a radar system, a module for improving a radar system and an improved radar system that are more efficient than current radar systems and methods of using same. Specifically, in the context of space-time adaptive processing at high angle-doppler resolutions, this advanced radar system utilizes an improved estimator of the interference covariance matrix together with the plug-in whiten-then-match filter. This improvement (a) roughly optimizes the output signal-to-interference-plus-noise, thereby increasing the probability of accurately detecting targets' angular positions and radial velocities, (b) maintains a roughly constant, and thus controllable, false alarm rate, and (c) sometimes associates data preprocessing steps with a Reed-Mallett-Brennan detection loss, providing a guideline for rejecting certain preprocessing steps. Collectively, these advancements signify a considerable leap forward in radar technology.

A system for generating target information for a multi-radar target simulator includes: a modelling unit configured to generate a plurality of objects so as to be located within a plurality of radar detection ranges of a front radar sensor; an object arranging unit configured to arrange the plurality of objects located in each of the plurality of radar detection ranges in a distance order and select at least two objects among the plurality of arranged objects based on an order close to the front radar sensor and the same travelling direction; and a simulator control unit configured to select at least two objects as targets from the at least two objects selected by the object arranging unit as targets and control a multi-radar target simulator by using information about said at least two selected targets.

An apparatus configured to: receive an input dataset indicative of radar signals, reflected from targets, received at an antenna; determine an objective function for evaluation over a plurality of points of a search space representing possible direction-of-arrival angles; evaluate the objective function for a first candidate number of targets; perform a first evaluation of a branch metric function based on a second candidate number of targets, wherein the branch metric function is indicative of a change in the objective function; and if the branch metric function is greater than a predetermined threshold, then evaluate the objective function for the second candidate number of targets; if the branch metric function is less than the predetermined threshold, then evaluate the objective function for the first candidate number of targets, wherein the evaluation is based on at least one of the first candidate number of targets having a different, second candidate direction-of-arrival angle.

Some examples of the disclosure are directed to implementing a passive and adaptive bistatic or multi-static radar system. Some examples of the disclosure are directed to using reflections from one or more navigational aids. Some examples of the disclosure are directed to generating a digital model of a physical environment to implement a deterministic passive radio system. Some examples of the disclosure are directed to collaborative approaches to identifying, locating, and track airborne objects.