Abstract: A system performs operations including receiving multi-dimensional single-look data from a sensor, applying multi-dimensional complex weighting functions including apodizations from among a general class of such functions to the complex data, so as to induce nonlinear variations in the amplitude and phase of the multi-dimensional spectral image responses, forming a number of features per voxel across a number of multi-dimensional spectral image responses, and using a multi-dimensional non-parametric classifier to form features to discriminate main lobe from sidelobe imaged voxels with the weighting function applied to received data. The operations include identifying each voxel by processing a set of transforms from the multi-dimensional complex weighting functions and outputting a multi-dimensional main lobe binary image, representing main lobe versus sidelobe locations.

Abstract: A system performs operations including receiving pairs of sensor signals indicative of imaging of an environment, each pair of sensor signals including (i) a first sensor signal received from a first sensor and including first spatial coordinates and a first signal characteristic and (ii) a second sensor signal including second spatial coordinates and a second signal characteristic. The operations include identifying valid pairs of sensor signals, including determining that an address including the first coordinates of the first sensor signal of a given pair and the second coordinates of the second sensor signal of the given pair corresponds to an admissible address in a set of admissible addresses stored in a data storage.

Abstract: A low cost, all weather, high definition RF radar system for an autonomous vehicle is described. The high definition RF radar system generates true target object data suitable for imaging, scene understanding, and all weather navigation of the autonomous vehicle. The high definition RF radar system includes a pair of independent orthogonal linear arrays. Data from both linear arrays is fed to a processor that performs data association to form true target detections and target positions. A Boolean association method for determining true target detections and target positions reduces many of the ghosts or incorrect detections that can produce image artifacts. The high definition RF radar system provides near optimal imaging in any dense scene for autonomous vehicle navigation, including during visually obscured weather conditions such as fog.