The present disclosure discloses a method for inverting aerosol components using a LiDAR ratio and a depolarization ratio, including: S1. identifying sand dust, a spherical aerosol and a mixture of the sand dust and the spherical aerosol based on a depolarization ratio; S2. calculating a proportion of the sand dust in the mixture of the sand dust and the spherical aerosol; and S3. identifying soot and a water-soluble aerosol in the spherical aerosol based on a LiDAR ratio. In the present disclosure, only a wavelength with a polarization channel is needed, to identify the aerosol components, achieving high accuracy with low detection costs.

The present disclosure describes methods and systems for measuring crosswind speed by optical measurement of laser scintillation. One method includes projecting radiation into a medium, receiving, over time, with a photodetector receiver, a plurality of scintillation patterns of scattered radiation, comparing cumulative a radiation intensity for each received scintillation pattern of the received plurality of scintillation patterns, and measuring a cumulative weighted average cross-movement within the medium using the compared cumulative radiation intensities.

The present disclosure describes methods and systems for measuring crosswind speed by optical measurement of laser scintillation. One method includes projecting radiation into a medium, receiving, over time, with a photodetector receiver, a plurality of scintillation patterns of scattered radiation, comparing cumulative a radiation intensity for each received scintillation pattern of the received plurality of scintillation patterns, and measuring a cumulative weighted average cross-movement within the medium using the compared cumulative radiation intensities.

A wind estimation system for an aircraft includes a first sensor configured to sense a first position associated with an aircraft control component in a wind condition, a second sensor configured to sense a first configuration associated with a rotor system of the aircraft in the wind condition, and at least one controller in communication with at least one of the first sensor or the second sensor. The at least one controller is configured to determine a tip-path-plane angle of the aircraft based on the first position and the first configuration, and determine at least one of a current wind speed or current wind direction based on the tip-path-plane angle.

A wind estimation system for an aircraft includes a first sensor configured to sense a first position associated with an aircraft control component in a wind condition, a second sensor configured to sense a first configuration associated with a rotor system of the aircraft in the wind condition, and at least one controller in communication with at least one of the first sensor or the second sensor. The at least one controller is configured to determine a tip-path-plane angle of the aircraft based on the first position and the first configuration, and determine at least one of a current wind speed or current wind direction based on the tip-path-plane angle.

A control device (900) includes an acquirer (910) that acquires information expressing weather related to a port that is a location at which a landing of an aircraft is scheduled, and a controller (930) that causes an alerter to perform a behavior corresponding to the weather expressed in the acquired information. The alerter performs an alert related to the landing of the aircraft.

A meteorological lidar performs highly precise meteorological observation by primarily removing elastically scattered light and by detecting rotational Raman-scattered light without filtering it out. The meteorological lidar according to embodiments measures scattered light of a laser beam, and includes: a diffraction grating diffracting rotational Raman-scattered light contained in scattered light in accordance with the wavelength of rotational Raman-scattered light; a detector detecting the diffracted rotational Raman-scattered light; and a removing element primarily removing elastically scattered light of a specific wavelength contained in the scattered light.

A meteorological lidar performs highly precise meteorological observation by primarily removing elastically scattered light and by detecting rotational Raman-scattered light without filtering it out. The meteorological lidar according to embodiments measures scattered light of a laser beam, and includes: a diffraction grating diffracting rotational Raman-scattered light contained in scattered light in accordance with the wavelength of rotational Raman-scattered light; a detector detecting the diffracted rotational Raman-scattered light; and a removing element primarily removing elastically scattered light of a specific wavelength contained in the scattered light.

The technology relates to determining general weather conditions affecting the roadway around a vehicle, and how such conditions may impact driving and route planning for the vehicle when operating in an autonomous mode. For instance, the on-board sensor system may detect whether the road is generally icy as opposed to a small ice patch on a specific portion of the road surface. The system may also evaluate specific driving actions taken by the vehicle and/or other nearby vehicles. Based on such information, the vehicle's control system is able to use the resultant information to select an appropriate braking level or braking strategy. As a result, the system can detect and respond to different levels of adverse weather conditions. The on-board computer system may share road condition information with nearby vehicles and with remote assistance, so that it may be employed with broader fleet planning operations.

The technology relates to determining general weather conditions affecting the roadway around a vehicle, and how such conditions may impact driving and route planning for the vehicle when operating in an autonomous mode. For instance, the on-board sensor system may detect whether the road is generally icy as opposed to a small ice patch on a specific portion of the road surface. The system may also evaluate specific driving actions taken by the vehicle and/or other nearby vehicles. Based on such information, the vehicle's control system is able to use the resultant information to select an appropriate braking level or braking strategy. As a result, the system can detect and respond to different levels of adverse weather conditions. The on-board computer system may share road condition information with nearby vehicles and with remote assistance, so that it may be employed with broader fleet planning operations.