Disclosed herein are examples of ladar systems and methods where data about a plurality of ladar returns from prior ladar pulse shots gets stored in a spatial index that associates ladar return data with corresponding locations in a coordinate space to which the ladar return data pertain. This spatial index can then be accessed by a processor to retrieve ladar return data for locations in the coordinate space that are near a range point to be targeted by the ladar system with a new ladar pulse shot. This nearby prior ladar return data can then be analyzed by the ladar system to help define a shot energy for use by the ladar system with respect to the new ladar pulse shot.

Systems and methods are disclosed where a ladar system synthetically fills a ladar frame. A ladar transmitter can employ compressive sensing to interrogate a subset of range points in a field of view. Returns from this subset of range points correspond to a sparse ladar frame, and interpolation can be performed on these returns to synthetically fill the ladar frame.

Systems and methods are disclosed where a ladar system synthetically fills a ladar frame. A ladar transmitter can employ compressive sensing to interrogate a subset of range points in a field of view. Returns from this subset of range points correspond to a sparse ladar frame, and interpolation can be performed on these returns to synthetically fill the ladar frame.

Optical modality configured to simulate measurements of the radar cross-section of targets, dimensioned to be conventionally-measured in the RF-portion of the electromagnetic spectrum, with sub-micron accuracy. A corresponding compact optical system, with a foot-print comparable with a tabletop, employing optical interferometric time-of-flight approach to reproduce, on a substantially shorter time-scale, radar-ranging measurements ordinarily pertaining to the range of frequencies that are at least 10.sup.3 times lower than those employed in the conventional RF-based measurement.

Disclosed herein are examples of ladar systems and methods where data about a plurality of ladar returns from prior ladar pulse shots gets stored in a spatial index that associates ladar return data with corresponding locations in a coordinate space to which the ladar return data pertain. This spatial index can then be accessed by a processor to retrieve ladar return data for locations in the coordinate space that are near a range point to be targeted by the ladar system with a new ladar pulse shot. This nearby prior ladar return data can then be analyzed by the ladar system to help define a parameter value for use by the ladar system with respect to the new ladar pulse shot. Examples of such adaptively controlled parameter values can include shot energy, receiver parameters, shot selection, camera settings, and others.

Disclosed herein are examples of ladar systems and methods where data about a plurality of ladar returns from prior ladar pulse shots gets stored in a spatial index that associates ladar return data with corresponding locations in a coordinate space to which the ladar return data pertain. This spatial index can then be accessed by a processor to retrieve ladar return data for locations in the coordinate space that are near a range point to be targeted by the ladar system with a new ladar pulse shot. This nearby prior ladar return data can then be analyzed by the ladar system to help define a control setting for use by a ladar system camera.

Disclosed herein are examples of ladar systems and methods where data about a plurality of ladar returns from prior ladar pulse shots gets stored in a spatial index that associates ladar return data with corresponding locations in a coordinate space to which the ladar return data pertain. This spatial index can then be accessed by a processor to retrieve ladar return data for locations in the coordinate space that are near a range point to be targeted by the ladar system with a new ladar pulse shot. This nearby prior ladar return data can then be analyzed by the ladar system to help define a parameter value for use by the ladar system with respect to the new ladar pulse shot. Examples of such adaptively controlled parameter values can include shot energy, receiver parameters, shot selection, camera settings, and others.

The disclosure relates to methods, systems, and apparatuses for virtual sensor data generation and more particularly relates to generation of virtual sensor data for training and testing models or algorithms to detect objects or obstacles. A method for generating virtual sensor data includes simulating, using one or more processors, a three-dimensional (3D) environment comprising one or more virtual objects. The method includes generating, using one or more processors, virtual sensor data for a plurality of positions of one or more sensors within the 3D environment. The method includes determining, using one or more processors, virtual ground truth corresponding to each of the plurality of positions, wherein the ground truth comprises a dimension or parameter of the one or more virtual objects. The method includes storing and associating the virtual sensor data and the virtual ground truth using one or more processors.

Disclosed herein are examples of ladar systems and methods where data about a plurality of ladar returns from prior ladar pulse shots gets stored in a spatial index that associates ladar return data with corresponding locations in a coordinate space to which the ladar return data pertain. This spatial index can then be accessed by a processor to retrieve ladar return data for locations in the coordinate space that are near a range point to be targeted by the ladar system with a new ladar pulse shot. This nearby prior ladar return data can then be analyzed by the ladar system to help adapt a shot selection for use by the ladar system with respect to new ladar pulse shots.

An environment sensing method includes the following steps, carried out by a data processor a) defining an occupancy grid comprising a plurality of cells; b) acquiring at least one measurement result from a distance sensor, representative of the distance of one or more nearest targets; and c) computing an occupation probability of the cells of the occupancy grid by applying to the measurement an inverse sensor model stored in a memory device in the form of a data structure representing a plurality of model grids associated to respective distance measurement results, at least some cells of a model grid corresponding to a plurality of contiguous cells of the occupancy grid belonging to a same of a plurality of angular sectors into which the field of view of the distance sensor is divided, and associating a same occupation probability to each one of the plurality of cells. An apparatus programmed or configured for carrying out the environment sensing method and a computer-implemented method of computing an inverse sensor model suitable for carrying out the environment sensing method are also provided.