CN114814770A - Data analysis method based on radar - Google Patents

Abstract

The invention discloses a data analysis method based on radar, which comprises the following specific steps: determining the position of a target by using a radar, wherein the position comprises the distance and angle information of the target; and extracting a preliminary signal of the target according to the target distance and angle information determined by the radar, and filtering the preliminary signal to obtain a processed signal. The invention can realize non-contact type long-time continuous target detection, has higher accuracy and provides more choices for detection.

Description

Data analysis method based on radar

Technical Field

The invention relates to the field of data analysis and detection, in particular to a data analysis method based on radar.

Background

Today, artificial intelligence is gaining importance, and various behaviors such as machine behaviors and the like exist, and the artificial intelligence can be used for simulating various behaviors of a human to replace the human to carry out labor. However, how to accurately identify certain behaviors and how to make accurate judgment on the behaviors are troubling current artificial intelligence practitioners.

Disclosure of Invention

The invention aims to provide a data analysis method based on radar so as to realize non-contact and long-time continuous detection of human bodies.

In order to solve the technical problem, the invention provides a data analysis method based on radar, which comprises the following specific steps:

determining the position of a target by using a radar, wherein the position comprises the distance and angle information of the target;

and extracting a preliminary signal of the target according to the target distance and angle information determined by the radar, and filtering the preliminary signal to obtain a processed signal.

Further, the step of the radar determining the target position comprises:

performing FFT processing on ADC data in target position information acquired by a radar in a distance dimension;

performing static clutter removal processing on the result of the distance dimension FFT processing, performing CFAR detection on the result after the static clutter removal processing, and determining the distance information of the target;

and after obtaining the target distance information, extracting multi-channel data of the distance unit where the target is located to carry out DOA estimation to obtain target angle information.

Further, the processing step of static clutter removal is: and static object interference is removed in a multi-frame accumulation mode, and the energy of a distance unit where the target is located is enhanced.

Further, the static clutter removal process employs a band-pass filter.

Further, the formula of the radar ranging is as follows:

wherein chirp represents a chirp signal, rangeFFTi represents an average value of one-dimensional FFTs of all chirp in an ith frame, RangeFFTi represents a result after static clutter removal, and N represents a sliding window size for removing the static clutter; CFAR detection was performed on RangeFFTi.

Further, the specific step of extracting the preliminary signal of the target is as follows:

extracting data of each channel of a distance unit where a target is located;

carrying out DBF processing on the angle of the target on the extracted multi-channel data;

extracting the phase of the distance unit where the target is located after the DBF processing is carried out, and carrying out phase unwrapping;

and calculating the phase difference of the phases between the front frame and the rear frame of the distance unit where the target is located.

Further, a behavior determination method is characterized by further comprising, based on a radar-based data analysis method: and extracting discrimination characteristics from the processed signals to judge whether the behaviors are abnormal.

Further, the distinguishing features are standard deviation of the processed signal and energy ratio of frequency spectrum of the processed signal and the preliminary signal.

Further, the standard deviation S of the processed signal and the calculation formula of the energy ratio P of the frequency spectrum of the processed signal and the preliminary signal are respectively as follows:

where Breath denotes the processed signal, N denotes the length of the processed signal, VitalFFT denotes the result of the preliminary signal FFT, N denotes the start frequency bin of the frequency range, and M denotes the cut-off frequency bin of the frequency range.

Further, the method for determining the behavior abnormality includes:

counting the values of S and P under abnormal conditions and normal conditions, and setting thresholds Sthre and Pthre according to the counting result;

and (6) calculating S, P value of the current moment, and judging that the behavior abnormality phenomenon exists at the current moment when the values of S and P are smaller than the set threshold value.

Compared with the prior art, the invention at least has the following beneficial effects: by using the millimeter radar, different influences of the target position on the radar phase are detected, whether an abnormal phenomenon occurs or not is judged, the target can be detected continuously for a long time in a non-contact manner, the accuracy is high, and more choices are provided for abnormal detection.

Drawings

FIG. 1 is a flow chart of a method of data analysis in accordance with an embodiment of the present invention;

FIG. 2 is a flow chart of a method for locating an object in accordance with an embodiment of the present invention;

FIG. 3 is a flow chart of a method for extracting a preliminary target signal according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a radar transmission waveform in accordance with an embodiment of the present invention.

Detailed Description

The radar-based data analysis method of the present invention will be described in more detail below with reference to schematic drawings, in which preferred embodiments of the present invention are shown, it being understood that a person skilled in the art may modify the invention described herein while still achieving the advantageous effects of the present invention. Accordingly, the following description should be construed as broadly as possible to those skilled in the art and not as limiting the invention.

The invention is more particularly described in the following paragraphs with reference to the accompanying drawings by way of example. Advantages and features of the present invention will become apparent from the following description and from the claims. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.

As shown in fig. 1, an embodiment of the present invention provides a data analysis method based on radar, including the following specific steps:

determining the position of a target by using a radar, wherein the position comprises the distance and angle information of the target;

and extracting a preliminary signal of the target according to the target distance and angle information determined by the radar, and filtering the preliminary signal to obtain a processed signal.

When the radar is used for detecting the state of a target, the distance and angle information of the target is measured, a primary signal of the target is extracted from the distance and angle information, a processed signal is obtained from the primary signal, and the abnormal state of the target is detected through the processed signal. Referring to fig. 4, the present invention employs a 77G carrier frequency millimeter wave radar, the waveform is a sawtooth wave, and the frame period is 50ms, so as to continuously monitor the target state.

The following is a list of preferred embodiments of the radar-based data analysis method for clearly illustrating the contents of the present invention, and it should be understood that the contents of the present invention are not limited to the following embodiments, and other modifications by conventional technical means of those skilled in the art are within the scope of the idea of the present invention.

Referring to fig. 2, in one embodiment, the step of determining the target position by the radar includes:

performing FFT processing on ADC data in target position information acquired by a radar in a distance dimension;

performing static clutter removal processing on the result of the distance dimension FFT processing, performing CFAR detection on the result after the static clutter removal processing, and determining the distance information of the target;

and after obtaining the target distance information, extracting multi-channel data of the distance unit where the target is located to carry out DOA estimation to obtain target angle information. Mixing the received signals and the local oscillator signals to obtain ADC original data, and performing FFT calculation on each Chirp signal to obtain a distance FFT result oneDFFT, wherein 64 Chirps are obtained; the FFT is a high-efficiency algorithm of DFT, called fast Fourier transform, which is one of the most basic methods in time-frequency domain transform analysis; the ADC is an analog-to-digital converter and converts continuous signals in an analog form into discrete signals in a digital form; the CFAR detection is constant false alarm rate detection, in radar signal detection, when the external interference intensity changes, the radar can automatically adjust the sensitivity of the radar, so that the false alarm probability of the radar is kept unchanged, and the characteristic is called constant false alarm rate characteristic; DOA estimation is also called angular spectrum estimation, or angle of arrival estimation, and aims to estimate which transmitter is working and the direction in which the transmitter is located, in short, the direction in which the own radar receives incoming waves from a target transmitter is used for estimation.

The processing steps of the static clutter removal are as follows: and static object interference is removed in a multi-frame accumulation mode, and the energy of a distance unit where the target is located is enhanced. In the embodiment, the static clutter removal method is used for removing static object interference, so that the radar can conveniently detect the target distance.

In one embodiment, the static clutter removal process employs a band pass filter. Filtering the preliminary signal to remove the interference of other signals to obtain a processed signal; a band-pass filter is adopted in the static clutter removal process, and the band-pass range is the range of the frequency of the primary signal; in a preferred embodiment, the frequency band range of the preliminary signal is generally 0.2Hz-0.9Hz, so the invention can obtain the processed signal by filtering with an IIR digital filter with the passband ranging from 0.2Hz-0.9 Hz.

The radar ranging formula is as follows:

wherein chirp represents a chirp signal, rangeFFTi represents an average value of one-dimensional FFTs of all chirp in an ith frame, RangeFFTi represents a result after static clutter removal, and N represents a sliding window size for removing the static clutter; CFAR detection was performed on RangeFFTi. In the present embodiment, for example, Nchirp 64 indicates that the number of chips of one frame is 64, and N32 indicates the number of sliding window frames for removing static clutter, and the target distance is determined by detecting the sliding window frames within a set distance range.

Referring to fig. 3, in an embodiment, the step of extracting the preliminary signal of the target is as follows;

extracting data of each channel of a distance unit where a target is located;

carrying out DBF processing on the angle of the target on the extracted multi-channel data;

extracting the phase of the distance unit where the target is located after the DBF processing is carried out, and carrying out phase unwrapping;

and calculating the phase difference of the phases between the front frame and the rear frame of the distance unit where the target is located. Performing static clutter removal processing on the obtained distance dimension FFT result, and traversing the processed result at an angle interval of 1 degree by using a DBF algorithm to obtain an angle spectrum, wherein the point with the strongest energy of the angle spectrum is used as a target angle; DBF denotes digital beam forming or digital beam synthesis, and the digital beam forming technology is a product of combining the antenna beam forming principle with the digital signal processing technology, and is widely applied to the field of array signal processing.

Preferably, the behavior determination method is based on a radar-based data analysis method, and further includes: and extracting discrimination characteristics from the processed signals to judge whether the behaviors are abnormal. And extracting the distinguishing features in the processed signals, and judging the state of the target behavior according to the distinguishing features.

In one embodiment, the discriminant features are a standard deviation of the processed signal and an energy ratio of a frequency spectrum of the processed signal to the preliminary signal. And comparing the standard deviation of the processed signal and the energy ratio of the primary signal spectrum with a normal value to judge whether the abnormality occurs.

In one embodiment, the standard deviation S of the processed signal and the calculation formula of the energy ratio P of the frequency spectrum of the processed signal and the preliminary signal are respectively as follows:

where Breath denotes the processed signal, N denotes the length of the processed signal, VitalFFT denotes the result of the preliminary signal FFT, N denotes the start frequency bin of the frequency range, and M denotes the cut-off frequency bin of the frequency range. N is 60, and represents the number of processed signal points used for determination, and performs FFT of 256 points on the preliminary signal Vital to obtain a preliminary signal spectrum VitalFFT, where N is 3 and M is 12, which are the start unit and the end unit of the preliminary signal band, respectively.

In one embodiment, the method for determining is as follows:

counting the values of S and P in abnormal and normal states, and setting thresholds Sthre and Pthre according to the counting result;

and (6) calculating S, P value of the current time, and judging that the current time has an abnormal phenomenon as long as the values of S and P are both smaller than the set threshold value. And when the standard deviation of the processed signal and the energy ratio of the processed signal to the primary signal spectrum are both smaller than a set value, judging that an abnormal condition occurs.

The invention can be widely applied to various scenes such as medical detection, precision instrument processing, intelligent home, old people health monitoring, pet health monitoring and the like.

In summary, the millimeter radar is used for detecting different influences of the target position on the radar phase, judging whether an abnormal phenomenon occurs or not, realizing non-contact type long-time continuous target detection, having higher accuracy and providing more choices for abnormal detection.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (10)

1. A data analysis method based on radar is characterized by comprising the following specific steps:

determining the position of a target by using a radar, wherein the position comprises the distance and angle information of the target;

and extracting a preliminary signal of the target according to the target distance and angle information determined by the radar, and filtering the preliminary signal to obtain a processed signal.

2. The radar-based data analysis method of claim 1, wherein the radar determines the target location by:

performing FFT processing on ADC data in target position information acquired by a radar in a distance dimension;

performing static clutter removal processing on the result of the distance dimension FFT processing, performing CFAR detection on the result after the static clutter removal processing, and determining the distance information of the target;

and after obtaining the target distance information, extracting multi-channel data of the distance unit where the target is located to carry out DOA estimation to obtain target angle information.

3. The radar-based data analysis method of claim 2, wherein the static clutter removal is performed by: and static object interference is removed in a multi-frame accumulation mode, and the energy of a distance unit where the target is located is enhanced.

4. The radar-based data analysis method of claim 3, wherein the static clutter removal process employs a band pass filter.

5. The radar-based data analysis method of claim 1, wherein the radar ranging is formulated as follows:

wherein chirp represents a chirp signal, rangeFFTi represents an average value of one-dimensional FFTs of all chirp in an ith frame, RangeFFTi represents a result after static clutter removal, and N represents a sliding window size for removing the static clutter; CFAR detection was performed on RangeFFTi.

6. The radar-based data analysis method of claim 1, wherein the step of extracting the preliminary signal of the target comprises:

extracting data of each channel of a distance unit where a target is located;

carrying out DBF processing on the angle of the target on the extracted multi-channel data;

extracting the phase of the distance unit where the target is located after the DBF processing is carried out, and carrying out phase unwrapping;

and calculating the phase difference of the phases between the front frame and the rear frame of the distance unit where the target is located.

7. A behavior determination method, based on the radar-based data analysis method according to any one of claims 1 to 6, further comprising: and extracting discrimination characteristics from the processed signals to judge whether the behaviors are abnormal.

8. The radar-based data analysis method of claim 7, wherein the discriminative features are a standard deviation of the processed signal and an energy ratio of a spectrum of the processed signal to the preliminary signal.

9. The radar-based data analysis method of claim 8, wherein the standard deviation S of the processed signal and the calculation formula of the energy ratio P of the spectrum of the processed signal to the preliminary signal are respectively:

where Breath denotes the processed signal, N denotes the length of the processed signal, VitalFFT denotes the result of the preliminary signal FFT, N denotes the start frequency bin of the frequency range, and M denotes the cut-off frequency bin of the frequency range.

10. The radar-based data analysis method of claim 9, wherein the behavioral abnormality is determined by:

counting the values of S and P under abnormal conditions and normal conditions, and setting thresholds Sthre and Pthre according to the counting result;

and (6) calculating S, P value of the current moment, and judging that the behavior abnormality phenomenon exists at the current moment when the values of S and P are smaller than the set threshold value.

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