Signal Processing Method and Radar System of Micro-deformation Observation Radar System

Abstract

The present application relates to a signal processing method and radar system of a small deformation observation radar system of a target. The method includes: sequentially performing the adjacent multi-target separation algorithm, the accurate phase extraction of the adjacent target and the time difference interference processing on the radar echo data obtained by multiple sources and multiple receivers, so that the shape of multiple targets with the same radial distance but different lateral positions can be accurately estimated. Variables, in order to achieve high-precision, high-frequency, non-contact multi-point simultaneous measurement of dense multi-target micro-deformation, and has broad application prospects in complex bridges, iron towers, buildings and other fields.

Description

technical field [0001] The present application relates to the technical field of infrastructure structure security and precision measurement, in particular to a signal processing method and a radar system of a target micro-deformation observation radar system. Background technique [0002] Bridges, tunnels, iron towers, buildings, dams, slopes and other targets will be deformed under the action of natural external forces (gravity, wind, hydraulic, temperature stress, etc.) In a limited time, it may cause irreversible structural damage, and then cause loss of life and property. Therefore, it is of great significance to conduct precise observation of the small deformation of these important objects. Bridges, electric power, mining, water conservancy and other industry standards also require high-precision deformation Measurements set clear requirements. [0003] At present, deformation measurement technology is mainly divided into contact and non-contact deformation measureme...

AI Technical Summary

Problems solved by technology

[0004] (1) Measurement is time-consuming and costly

When detecting the deformation of large bridges and high towers, if conventional single-point measurement sensors are used, multi-point installation and fixation, long-distance cable laying, and one-by-one debugging and optimization are required. Therefore, the workload is large, the construction cost is high, and the system robustness is poor.

There are still great safety risks when climbing and working in the field, and it is difficult to meet the time-limited needs of emergency rescue, traffic repair and measurement;

[0005] (2) Low degree of intelligence

Many conventional sensors require manual calibration, manual installation of targets, and manual reading of data one by one, resulting in problems such as large system delay, low reliability, and weak informatization, making it difficult to adapt to the requirements for intelligent sensors in the field of health monitoring in the future;

[0006] (3) Poor environmental adaptability

[0008] (1) One-dimensional deformation measurement radar can only measure the deformation of objects with different radial distances. If two objects have the same radial distance but different lateral positions, then this radar cannot distinguish between the two, although it can also calculate Get a set of deformation values, but this set of data cannot accurately describe the deformation of any of the two objects;

[0009] (2) Although the two-dimensional deformation radar can solve the multi-target resolution problem with the same radial distance and different lateral positions, the price paid is that the refresh rate of deformation measurement (the number of times of measuring object deformation per second) is significantly reduced, so it can only detect extremely Measurement of slow objects (such as dams, slopes, etc.), cannot be used for deformation measurement of rapidly deforming objects such as bridges and iron towers

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