A machine includes a rotational sensor configured to sense rotation of an upper frame of the machine relative to a lower frame of the machine. The machine also includes a three-dimensional position sensor spaced from an axis of rotation of the upper frame relative to the lower frame. The machine can also include a number of additional sensors including sensors to detect track movement, imaging sensors, ranging sensors, IMUs, linear displacement sensors and/or the like. A computing system receives the various inputs from the sensors and fuses the data to determine state information for the machine.

An antenna alignment apparatus may include magnetic field sensors as an alternative to or in addition to GNSS sensors. The magnetic field sensors may measure the earth's magnetic fields at corresponding locations, and a processor may use the measurements to calculate at least one of a roll, tilt, or azimuth of an antenna. For an optical alignment, the antenna alignment apparatus may, additionally or alternately, include a reference object (e.g., a printed mark or a physical stud) located within a field of view of a camera. A location of the reference object may indicate the alignment of the antenna vis-a-vis the structures within the field of view.

An antenna alignment apparatus may include magnetic field sensors as an alternative to or in addition to GNSS sensors. The magnetic field sensors may measure the earth's magnetic fields at corresponding locations, and a processor may use the measurements to calculate at least one of a roll, tilt, or azimuth of an antenna. For an optical alignment, the antenna alignment apparatus may, additionally or alternately, include a reference object (e.g., a printed mark or a physical stud) located within a field of view of a camera. A location of the reference object may indicate the alignment of the antenna vis-a-vis the structures within the field of view.

This disclosure relates generally to root zone moisture estimation for vegetation cover using remote sensing. Conventionally, it is challenging to estimate root zone soil moisture using only satellite data. Moreover, estimation of soil moisture under vegetation cover based on bare surface soil moisture and vegetation parameters is not available. The disclosed method and system facilitate estimation of an ensemble of soil moisture under vegetation cover and root zone soil moisture using process based soil water balance for spatial estimation of root zone soil moisture. The system estimates bare surface soil moisture for different soil types/textures using the baseline bare surface model and soil properties derived from satellite data and in-situ sensors. The method further provides temporal spatially distributed soil moisture inputs to an intelligent irrigation management/information system which is very important to reduce and regulate water consumption.

This disclosure relates generally to root zone moisture estimation for vegetation cover using remote sensing. Conventionally, it is challenging to estimate root zone soil moisture using only satellite data. Moreover, estimation of soil moisture under vegetation cover based on bare surface soil moisture and vegetation parameters is not available. The disclosed method and system facilitate estimation of an ensemble of soil moisture under vegetation cover and root zone soil moisture using process based soil water balance for spatial estimation of root zone soil moisture. The system estimates bare surface soil moisture for different soil types/textures using the baseline bare surface model and soil properties derived from satellite data and in-situ sensors. The method further provides temporal spatially distributed soil moisture inputs to an intelligent irrigation management/information system which is very important to reduce and regulate water consumption.

A system measures tracking ability of a service animal using a location sensor to generate location data and a measurement unit measuring auxiliary data related to movement of the animal while tracking a known path. A computer calculates a rank metric representing a measure of similarity between animal location data from the location sensor and stored target data defining the known path. The computer also calculates an animal signature representative of a relationship between the auxiliary data and the rank metric for different instantaneous values of the rank metric. When tracking an unknown path, a confidence metric is calculated based on the animal signature and the auxiliary data collected while tracking such that the confidence metric represents a quantitative measure of the ability of the service animal to track the unknown path.

A system measures tracking ability of a service animal using a location sensor to generate location data and a measurement unit measuring auxiliary data related to movement of the animal while tracking a known path. A computer calculates a rank metric representing a measure of similarity between animal location data from the location sensor and stored target data defining the known path. The computer also calculates an animal signature representative of a relationship between the auxiliary data and the rank metric for different instantaneous values of the rank metric. When tracking an unknown path, a confidence metric is calculated based on the animal signature and the auxiliary data collected while tracking such that the confidence metric represents a quantitative measure of the ability of the service animal to track the unknown path.

A wearable training computer includes a global navigation satellite system (GNSS) antenna arrangement configured to provide a group of antenna configurations for receiving a GNSS signal, wherein each antenna configuration provides different radio frequency properties. The wearable training computer further includes a measurement circuitry configured to measure performance of the GNSS antenna and a processing circuitry configured to select, based on at least an activity type of a user of the wearable training computer, a subset of the antenna configurations from the group of the antenna configurations, and further configured to select, from the subset of the antenna configurations based on the measured GNSS antenna performance, an antenna configuration for receiving the GNSS signal.

A wearable training computer includes a global navigation satellite system (GNSS) antenna arrangement configured to provide a group of antenna configurations for receiving a GNSS signal, wherein each antenna configuration provides different radio frequency properties. The wearable training computer further includes a measurement circuitry configured to measure performance of the GNSS antenna and a processing circuitry configured to select, based on at least an activity type of a user of the wearable training computer, a subset of the antenna configurations from the group of the antenna configurations, and further configured to select, from the subset of the antenna configurations based on the measured GNSS antenna performance, an antenna configuration for receiving the GNSS signal.

There is provided a positioning system for a work machine using RTK positioning that uses a satellite positioning system, the positioning system including: a sensor controller that is a calculation unit that calculates a position of an antenna, of the satellite positioning system, disposed in the work machine based on a position of working equipment, of the work machine, aligned with a known reference point PR positioned at a work site; and a monitor controller that is an initialization control unit that outputs a control command that causes a receiver, of the satellite positioning system, that performs positioning calculation by the RTK positioning to execute initialization processing of the positioning calculation in which an integer value bias of each satellite and the position of the antenna of the satellite positioning system are unknown, by using the calculated position of the antenna of the satellite positioning system.