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Signal processing method for anti-collision system in complex environment of unmanned vehicles based on combined waveform

A technology for unmanned vehicles and complex environments, applied in the field of signal processing, to solve problems such as collision avoidance in complex environments

Active Publication Date: 2021-02-19
DALIAN ROILAND SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problem of anti-collision in the complex environment of unmanned vehicles, the present invention proposes a signal processing method based on combined waveforms for the complex environment anti-collision system of unmanned vehicles to realize the calculation of the speed of obstacles, etc.

Method used

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  • Signal processing method for anti-collision system in complex environment of unmanned vehicles based on combined waveform
  • Signal processing method for anti-collision system in complex environment of unmanned vehicles based on combined waveform
  • Signal processing method for anti-collision system in complex environment of unmanned vehicles based on combined waveform

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Embodiment 1

[0021] Embodiment 1: A signal processing method for an unmanned vehicle complex environment anti-collision system based on a combined waveform, the combined waveform is a waveform composed of a triangular wave modulated FMCW signal and a constant frequency wave modulated CW signal, the first section is a triangular wave, and the second segment is a constant frequency wave;

[0022] The signal processing method includes the following steps:

[0023] S1. For each segment of the waveform, the IQ data collected by the A / D is subjected to time-frequency FFT transformation, and the time domain data is converted into frequency data;

[0024] S2. Use the complex modulus value after the FFT transformation of each segment of the waveform as the threshold detection CFAR, output the position of the threshold point, calculate the corresponding frequency value according to the point of the threshold, and thus obtain the frequency matrix at the corresponding point, and calculate at the same ...

Embodiment 2

[0038] Embodiment 2: As a supplement to Embodiment 1, for the unmanned vehicle to be able to avoid obstacles in a complex environment, it is required that the unmanned vehicle anti-collision millimeter-wave radar can realize the simultaneous detection of multiple targets. There are many main methods for realizing multi-target detection by millimeter waves. In this embodiment, a combination waveform using triangular waves and constant-frequency waves is used to realize the accurate detection function of multiple targets. In this embodiment, the central frequency of the millimeter wave is 24 GHz or 77 GHz, and the waveform adopts a waveform based on a combination of a CW signal modulated by a constant frequency wave and an FMCW signal modulated by a triangular wave. The waveform transmission form is that the first segment is a triangular wave, the working frequency ranges from 24.025GHz to 24.225GHz, the bandwidth is 200MHz, the triangular wave period is 20ms, the second segment ...

Embodiment 3

[0054] Embodiment 3: For the peak processing in each of the above solutions, this embodiment provides a peak processing method applied to driverless car signals:

[0055] Set a peak point threshold factor α, which is used to limit the absolute value of the difference between the detected maximum peak point crossing the threshold and the maximum peak point that appeared in the previous cycle, so that the absolute value of the difference must not be greater than the peak point threshold factor α:

[0056] The expression is as follows:

[0057] |L_max(k)-L_max(k-1)|≤α;

[0058]

[0059] Among them: L_max(k) is the coordinate of the maximum peak point crossing the threshold in k period, L_max(k-1) is the coordinate of the maximum peak point in the previous period, and k represents the kth moment; v max is the maximum speed of the driverless car, λ is the millimeter-wave radar wavelength, fs is the sampling rate, and N is the number of FFT points;

[0060] If at time k, the ab...

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Abstract

The invention relates to an unmanned automobile complex environment anticollision system signal processing method based on combination waveforms, belongs to the signal processing field and solves an unmanned automobile complex environment anticollision problem. The method is characterized by comprising steps that S1, for each waveform band, for IQ data acquired through an A / D, time frequency FFT transformation is carried out, and time domain data is converted into frequency data; S2, CFAR threshold detection of a complex modulus value of each waveform band after FFT transformation is carried out, the overthreshold point position is outputted, corresponding frequency values are calculated according to overthreshold points, frequency matrixes of the corresponding points are acquired, phase values corresponding to the overthreshold points of a constant frequency band are further calculated, and the phase matrixes of the corresponding points are acquired; and S3, for constant frequency waves, the speed matrix is acquired through calculation; for triangular waves, matching of an upper frequency sweep frequency matrix and a lower frequency sweep frequency matrix is carried out to calculate the distance and the speed, and the distance matrix and the speed matrix are acquired.

Description

technical field [0001] The invention belongs to the field of signal processing, and relates to a signal processing method for an unmanned vehicle complex environment anti-collision system based on combined waveforms. Background technique [0002] In recent years, with the development of the economy, the demand for transportation has increased day by day. Urban traffic congestion and frequent traffic accidents have become common problems faced by countries all over the world. The analysis of road traffic accidents shows that among the three links of drivers, cars and roads, the driver is the weakest link in reliability. Therefore, in recent years, unmanned cars that replace drivers have been born. Self-driving cars are also known as Driverless cars and computer-driven cars are intelligent cars that realize driverless driving through computer systems. [0003] In order to improve the safety of self-driving cars, self-driving cars rely on the cooperation of artificial intellig...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/931G01S7/41
CPCG01S7/41G01S13/931
Inventor 田雨农王鑫照
Owner DALIAN ROILAND SCI & TECH CO LTD
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