System and method for detecting object information based on synthetic aperture radar images

A method for detecting object information based on a synthetic aperture radar image, comprising:

• receiving an image of a synthetic aperture radar;
• extracting shadows defined as shaded areas where electromagnetic waves cannot reach in the received image;
• selecting moving an object with velocity among artificial objects that reflect electromagnetic waves in the received image, excluding a stationary object with no velocity and a shadow connected to the stationary object, to set moving target object;
• setting a boundary for the moving target object based on the maximum velocity of the moving target object;
• matching the extract shadow located within the set boundary with the moving target object using a machine learning model for the moving target object;
• loading beta angle information based on the matched moving target object and shadow in a matching result acquisition step;
• and
• calculating a moving velocity of the moving target object using a mathematical formula
• V
• moving
• ⁢
• velocity
• =
• V
• s
• ⁢
• Δ
• ⁢
• D
• R
• ⁢
• cos
• ⁢
• (
• β
• )
• (where Vs=velocity of synthetic aperture radar of a carrier, ΔD=distance between a matched shadow and a moving target object, R=distance between the synthetic aperture radar of the carrier and the moving target object, β=angle at which the moving target object is facing based on direction in which synthetic aperture radar views the moving target object), based on the acquired matching result.

A method for detecting object information in an object information detection system including a receiver module for receiving a synthetic aperture radar image and a processing module for extracting shadows defined as shaded areas where electromagnetic waves cannot reach in the received image and calculating information of natural objects that absorb at least a part of electromagnetic waves based on the extracted shadows, the method comprising:

• a filtering step of selecting shadows whose visible source object is not identified among the extracted shadows;
• a step of inferring or identifying natural objects from the shadows that passed through the filtering step using a machine learning model;
• and
• a step of calculating information of the inferred or identified natural objects based on a size or a shape of the extracted shadows,
• wherein the information of the inferred or identified natural objects includes the position, length, size, and occupied area of the natural objects.