A GPS filter-setting method comprises collecting, by a GPS filter-setting server, terminal information of a user terminal and GPS signal receiving environment information, setting, by the GPS filter-setting server, a filtering parameter used to filter an invalid GPS signal in the user terminal based on the collected terminal information of the user terminal and the GPS signal receiving environment information and transmitting, by the GPS filter-setting server, the set filtering parameter to the user terminal.

A first positioning portion, a calculator, and a second positioning portion are provided in an electronic device targeted for positioning. The first positioning portion obtains, by Doppler positioning, a candidate position which is a candidate for an initial position of the electronic device in code phase positioning from radio waves received from each of GPS satellites. The calculator calculates an index value indicating the magnitude of variation in code phase from a difference between a code phase obtained from the radio waves received from each of the GPS satellites and a code phase obtained based on a candidate position and a position of each GPS satellite. The second positioning portion performs the code phase positioning using ZCount or a candidate position according to the index value.

A first positioning portion, a calculator, and a second positioning portion are provided in an electronic device targeted for positioning. The first positioning portion obtains, by Doppler positioning, a candidate position which is a candidate for an initial position of the electronic device in code phase positioning from radio waves received from each of GPS satellites. The calculator calculates an index value indicating the magnitude of variation in code phase from a difference between a code phase obtained from the radio waves received from each of the GPS satellites and a code phase obtained based on a candidate position and a position of each GPS satellite. The second positioning portion performs the code phase positioning using ZCount or a candidate position according to the index value.

To make it possible to correct a current position detected by an autonomous traveling work machine to the correct position with a simple configuration. A robot lawn mower includes a first position detecting unit for detecting a current position by using odometry and a second position detecting unit for detecting a current position by using an image capture. When position detection accuracy of both of the first and second position detecting units decreases to less than or equal to a predetermined value, the robot lawn mower is controlled to travel to either of zones Z1 and Z2 in which the position detection accuracy of the second position detecting unit is relatively high, and when the robot lawn mower moves to either of the zones Z1 and Z2, a current position used for autonomous traveling is corrected to the current position detected by the second position detecting unit.

To make it possible to correct a current position detected by an autonomous traveling work machine to the correct position with a simple configuration. A robot lawn mower includes a first position detecting unit for detecting a current position by using odometry and a second position detecting unit for detecting a current position by using an image capture. When position detection accuracy of both of the first and second position detecting units decreases to less than or equal to a predetermined value, the robot lawn mower is controlled to travel to either of zones Z1 and Z2 in which the position detection accuracy of the second position detecting unit is relatively high, and when the robot lawn mower moves to either of the zones Z1 and Z2, a current position used for autonomous traveling is corrected to the current position detected by the second position detecting unit.

A method for capturing, by a host vehicle camera, an image of a leading vehicle, estimating a leading vehicle dimension and a first distance between a host vehicle and the leading vehicle in response to the image, receiving a data indicative of a traffic signal location and a traffic signal cycle state, determining a second distance between the host vehicle and the traffic signal, estimating a traffic signal view obstruction in response to the leading vehicle dimension, the first distance, and the second distance, and generating a graphical user interface indicative of the traffic signal cycle state in response to the traffic signal view obstruction.

A method including operating a vehicle in a medium. The vehicle is subject to advection due to movement of the medium. The method also includes measuring, using a navigation system, positions of a vehicle over time. The method also includes measuring, using a directional sensor, a course-through-medium over the time. The method also includes calculating, using the positions and the course-through-medium, a variation of a speed-over-ground of the vehicle over the time as a function of the course-through-medium over the time. The method also includes concurrently estimating, using the variation, 1) an average speed-through-medium for the vehicle over the time, and 2) an advection rate of the medium, and 3) an advection direction of the medium.

A method including operating a vehicle in a medium. The vehicle is subject to advection due to movement of the medium. The method also includes measuring, using a navigation system, positions of a vehicle over time. The method also includes measuring, using a directional sensor, a course-through-medium over the time. The method also includes calculating, using the positions and the course-through-medium, a variation of a speed-over-ground of the vehicle over the time as a function of the course-through-medium over the time. The method also includes concurrently estimating, using the variation, 1) an average speed-through-medium for the vehicle over the time, and 2) an advection rate of the medium, and 3) an advection direction of the medium.

An aerial vehicle system for mapping an object buried in a subterranean surface, the aerial vehicle system including an aerial vehicle, an electronic sensor, a processor, and a memory. The memory includes instructions, which when executed by the processor, cause the system to receive a first input data set by the electronic sensor, the first input data set based on an electromagnetic signal and geographic location data, generate a raw image based on the first input data set, and compare the raw image to a calibration data set, the calibration data set based on material calibration data. The material calibration data is based on unique spectral reflection patterns of an object in a controlled environment at predefined heights and subterranean conditions.

An aerial vehicle system for mapping an object buried in a subterranean surface, the aerial vehicle system including an aerial vehicle, an electronic sensor, a processor, and a memory. The memory includes instructions, which when executed by the processor, cause the system to receive a first input data set by the electronic sensor, the first input data set based on an electromagnetic signal and geographic location data, generate a raw image based on the first input data set, and compare the raw image to a calibration data set, the calibration data set based on material calibration data. The material calibration data is based on unique spectral reflection patterns of an object in a controlled environment at predefined heights and subterranean conditions.