Orthogonal cw radar weak motion optimization detection method

Abstract

The application discloses a weak motion optimization detection method of orthogonal CW radar, which comprises the following steps: through displacement pre-motion and collection of echo signals generated by the pre-motion, a reference ellipse is fitted to extract mismatch parameters caused by channel mismatch of the echo signals of the orthogonal CW radar, equivalent mathematical expectation of radar echo signals generated by a weak motion target reflection is calculated to realize compression of noise, the echo signals after compression of noise are calibrated by using the extracted mismatch parameters, and the effect of accurate detection of weak motion is achieved. Through pre-extraction of the channel mismatch parameters to obtain amplitude mismatch and phase mismatch parameters of the echo signals and mismatch compensation of the signals, each radar system only needs to perform channel mismatch parameter prediction once, noise is suppressed by using the probability statistical characteristics of the echo signals through noise compression based on the mathematical expectation, the lower limit of the weak displacement motion amplitude that can be detected by the radar is lower, and the detection precision is higher.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of radar motion detection, and particularly to a weak motion detection method for a quadrature continuous wave (CW) radar. BACKGROUND

[0002] Quadrature CW radar is sensitive to motion and is widely used in non-contact displacement extraction. However, the hardware of the quadrature CW radar system is not ideal, which causes amplitude and phase distortion (mismatch) of the echo signal caused by channel mismatch, as shown in formula (1). Figure 1 At the same time, when the target displacement motion amplitude is much smaller than the radar wavelength, the phase fluctuation of the echo signal is weak, and the signal-to-noise ratio is poor. These two problems deteriorate the accuracy of the quadrature CW radar demodulation of weak motion. For the channel mismatch problem, there is an elliptical calibration method, which extracts the amplitude and phase mismatch parameters by fitting the echo signal data points on an ellipse. However, in the weak motion scenario, the fitting ellipse arc is extremely short, the signal-to-noise ratio is poor, and accurate ellipse information cannot be obtained, resulting in the extraction of incorrect mismatch parameters. Moreover, the elliptical calibration calculation process is complex and not suitable for embedded implementation of the quadrature CW radar. For the low signal-to-noise ratio problem, the additive noise of the echo signal is often compressed and suppressed by a filter, such as denoising using convolution, or separating the signal and noise by subspace method. These methods have limited denoising degree and require large data calculation, which is not suitable for application in portable radar relying on embedded programming. SUMMARY

[0003] The present application proposes a weak motion detection method for a quadrature CW radar to solve the above problems in the prior art. The amplitude mismatch and phase mismatch parameters of the echo signal are obtained by pre-extracting the channel mismatch parameters, and the signal is compensated for mismatch. Each radar system only needs to perform channel mismatch parameter prediction at the same time, and the noise is suppressed by using the probability statistical characteristics of the echo signal based on the mathematical expectation of noise compression, so that the lower limit of the weak displacement motion amplitude that can be detected by the radar is lower, and the detection accuracy is higher.

[0004] The present application is implemented by the following technical solutions:

[0005] The present application relates to a weak motion detection method for a quadrature CW radar. After the displacement pre-motion and the collection of the echo signal generated by the pre-motion, a reference ellipse is formed by fitting to extract the mismatch parameters caused by the channel mismatch of the echo signal of the quadrature CW radar. The equivalent mathematical expectation of the radar echo signal generated by the weak motion target reflection is calculated to compress the noise, and then the mismatch parameters extracted are used to calibrate the channel of the echo signal after noise compression, thereby achieving the effect of accurately detecting weak motion.

[0006] The pre-motion refers to: before testing the weak motion, a long displacement motion of a strong reflection target (such as an angle reflection) is tested first, and the quadrature echo signals generated by the target motion are recorded, and each radar system only needs to do a pre-motion test.

[0007] The reference ellipse refers to: a phase diagram is drawn with the radar quadrature echo signals as the horizontal and vertical coordinates. Due to the amplitude mismatch and phase mismatch of the quadrature signals caused by channel mismatch, the phase diagram which should be circular appears as an ellipse, and the arc length of the ellipse depends on the length of the target motion. The pre-motion displacement is long enough, so its echo signal can fit to form a complete ellipse, and the complete ellipse can make the extraction of the mismatch parameters more accurate.

[0008] The mismatch parameters refer to: due to the non-ideal phase shifters, power dividers and mixers in the quadrature radar system hardware, the echo signal channel mismatch occurs, so that the quadrature echo signals which should have equal amplitude and a phase difference of 90° do not meet the conditions in amplitude and phase; the mismatch parameters include the amplitude mismatch parameter A e , which is the ratio of the amplitudes of the two quadrature echo signals, and the phase mismatch parameter , which is the difference between the phases of the two echo signals minus 90°.

[0009] The equivalent mathematical expectation calculation refers to: the collected echo signal is divided into M data segments with a length of S, and the average value of the S data points in each segment is taken to obtain an equivalent data point, and M data points are obtained to replace the original echo signal, where: M·S=L, L is the number of data points of the collected echo signal; according to the principle of random signal analysis, for a one-dimensional random signal c(n), its mathematical expectation When n is a large enough finite value (for example, n=S), For a deterministic signal s(n), the mathematical expectation represents the average value of the signal in the whole time, that is, E[s(n)]=average[s(n)], when the sampling rate is much larger than the rate of s(n) changing with time, it is considered that s(n) is almost constant in a segment, so And the mathematical expectation calculation satisfies the linearity, E[s(n)+c(n)]=E[s(n)]+E[c(n)].

[0010] The channel calibration refers to: the mismatch parameters A e and of the radar system are calculated by using the reference ellipse, and the quadrature echo signals are calibrated to signals with equal amplitudes and a phase difference of 90°.

[0011] The present application relates to a system for implementing the above method, comprising: a channel calibration and noise compression module, a direct current bias calibration module and a phase demodulation module, wherein: the channel calibration and noise compression module performs channel calibration processing according to the radar quadrature channel mismatch parameters extracted by pre-motion, and simultaneously calculates the compression additive noise by using the equivalent mathematical expectation of the echo signal, so as to compensate the quadrature echo signal amplitude and phase distortion and improve the signal-to-noise ratio thereof. The direct current bias calibration module removes the direct current bias voltage of the quadrature echo signal and normalizes the signal amplitude by using the quadrature of the echo signal. The phase demodulation module performs phase demodulation calculation according to the relationship between the phase information of the echo signal and the weak motion of the target, and finally extracts the weak motion of the target.

[0012] Technical effects

[0013] The present application adopts the pre-motion mode to accurately extract the mismatch parameters of the radar system with a small amount of data, complete channel calibration, and utilize the statistical characteristics of the determined signal and additive noise in the echo signal to propose the equivalent mathematical expectation calculation, realize the suppression of noise, and greatly improve the accuracy of radar detection of weak motion. Compared with the prior art, the present application overcomes the problems of inaccurate channel calibration and low signal-to-noise ratio when the radar tests weak motion, and conveniently and accurately calibrates the channel while removing noise by using the random signal characteristics of the additive noise in the echo signal. Overall, the present application effectively improves the ability and effect of the quadrature CW radar in detecting weak motion at a short distance. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 It is a block diagram of the existing quadrature CW radar system;

[0015] Figure 2 It is a flowchart of the present application;

[0016] Figure 3 It is a schematic diagram of the equivalent mathematical expectation calculation;

[0017] Figure 4 It is a diagram of the experimental setup for extracting channel mismatch parameters;

[0018] Figure 5 It is a schematic diagram of the experimental results for extracting channel mismatch parameters;

[0019] Figure 6 It is a diagram of the experimental setup for detecting the radial motion of the nanometer film curl;

[0020] Figure 7 It is a schematic diagram of the experimental results for detecting the radial motion of the nanometer film curl. DETAILED DESCRIPTION

[0021] As Figure 1The figure shows the orthogonal CW radar system involved in this embodiment, which includes: a transmitting antenna, a receiving antenna, a voltage-controlled oscillator (VCO), a power amplifier (PA), a low-noise amplifier (LNA), a downconversion module, a baseband operational amplifier (Amp), and a data acquisition card (DAQ). The downconversion module includes a 90-degree phase shifter and two mixers. The VCO generates a fixed-frequency continuous sine wave signal and splits it into two paths. One path serves as the local oscillator (LO) signal and is fed into the downconversion module. The other path is amplified by the power amplifier (PA) and transmitted by the transmitting antenna. After reaching the target, the signal is modulated by the target's slight motion and generates an echo. The receiving antenna receives the echo and feeds it into the downconversion module through the low-noise amplifier (LNA). In the down-conversion module, the echo signal is mixed with the original local oscillator signal and the local oscillator signal with a 90° phase shift, respectively, to output mismatched orthogonal echo signals I(t) and Q(t). After DAQ data acquisition, I(t) and Q(t) are obtained as digital signals I(n) and Q(n).

[0022] The mismatched orthogonal echo signals include: Where: A is the signal amplitude, A e and are the amplitude mismatch parameter and phase mismatch parameter of the orthogonal channel, λ is the orthogonal CW radar carrier wavelength, x(t) is the target weak motion, DC I / DC Q is the DC bias, N I (t) / N Q (t) is additive noise, which is usually defined as a zero-mean Gaussian random process, namely E[N I (t)]=0,E[N Q (t)]=0, It is the residual phase noise and can be ignored in the radar close-range detection scenario.

[0023] The digital signal includes: Where: To meet the calculation conditions of equivalent mathematical expectation, the sampling frequency f s Need to meet f s >>2d[x(t)] / λd[t].

[0024] like Figure 2 As shown in the figure, this embodiment involves a weak motion optimization detection method based on the above system, which completes the extraction of radar channel mismatch parameters and channel calibration and noise reduction of weak motion echo signals through the channel calibration and noise compression module, and then uses DC offset calibration to compensate the DC in the echo signal. I / DC Q, and normalize the amplitude A, and finally extract the weak motion x(n) contained in the phase through displacement demodulation.

[0025] like Figure 2 As shown, the extraction of radar channel mismatch parameters is to use radar to detect a sufficiently long displacement motion m(t) (for example, an amplitude of 0.5λ), and convert the echo data I cal (n) and Q cal (n) Stored in I cal (n) is the horizontal axis, Q cal (n) is the vertical coordinate, the data points are plotted in the two-dimensional phase diagram, a complete reference ellipse is formed by fitting, and the ellipse coefficient is extracted. Finally, the amplitude mismatch parameter A is calculated based on the ellipse equation. e and phase mismatch parameters

[0026] The channel calibration includes:

[0027] 1) Calculate the equivalent mathematical expectation: Divide the collected data I(n) / Q(n) into M segments, each segment is S in length, and make the equivalent mathematical expectation of the mth segment (1≤m≤M), that is, Where m = S / f s , which can be regarded as "slow time".

[0028] 2) Calibrate channel mismatch: Use the estimated Ae and to I E (m) / Q E (m) is calibrated, where: I E (m) is the reference value and no further calibration is required, i.e. I CE (m)=I E (m); in:

[0029] The DC bias calibration is to use The characteristics of I CE and Q CE Perform circle fitting and calculate the center of the circle (DC I ,DC' Q ) and the radius A of the circle, and finally the normalized orthogonal echo signal is obtained and in:

[0030] The displacement demodulation is to use the inverse tangent function to extract the phase and calculate the micro-motion trajectory contained in the phase, that is,

[0031] After specific experiments, Figure 4 The standard slide (Zaber T-NA08A50-KT04Μ) shown here generates two uniform linear motions, u(t) and m(t). The u(t) motion displacement is 0.0125 cm (= 0.01λ @ 24 GHz), which is used to simulate the traditional method of extracting mismatch parameters. The m(t) motion displacement is 0.625 cm (= 0.5λ @ 24 GHz), which is the pre-motion echo signal I proposed in this invention for extracting radar channel mismatch parameters. cal (n) and Q cal (n). The setting parameters are: the radar transmits a continuous sine wave signal with a frequency of f c =24GHz, carrier wavelength λ = 1.25cm, distance between the slide and the radar d0 = 15cm. The experimental results are as follows Figure 5 As shown, in Figure 5 In (a), due to the weak motion of u(t), the fitting forms an error ellipse, and the error mismatch parameters extracted by the error ellipse cannot be used for channel calibration. cal (n) and Q cal (n) forms a complete ellipse and perfectly matches the fitting ellipse. The radar channel mismatch coefficient calculated by the fitting ellipse is A e =1.06,

[0032] The radial displacement of the nanofilm is detected to test the detection accuracy of this method for weak target motion. The experimental scenario is as follows: Figure 6 As shown in (a), the radar setting parameters are: the radar transmits a continuous sine wave signal with a frequency of f c =24GHz, carrier wavelength λ = 1.25cm. DAQ sets the sampling frequency f s =10KHz, data segment length S=10. Figure 6 As shown in (b), the parameters of the nanofilm are: the length and width of the film before curling are both l = 150 μm, and the film performs a circular curling motion with a fixed diameter d = 52.9 μm. The curling displacement is captured by a high-speed camera. The duration of the movement is less than 0.2 seconds. The radar is facing the direction of the film, and the distance from the film is d0 = 8 cm. Figure 7 As shown, you can see that Figure 7 (a) and (c) are the spectrum and signal-to-noise ratio of the original I / Q signal, and the demodulated result using the original signal. Figure 7 (b) shows the spectrum and signal-to-noise ratio of the I / Q signal after channel calibration and noise compression. Channel calibration does not affect the signal-to-noise ratio, so noise compression suppresses additive noise by 2.3 dB and 2.1 dB, respectively.Figure 7 (d) is the demodulation result of the signal after only noise compression, and Figure 7 (c) can be seen that the root mean square error (RMSE) is reduced by 5.1 μm, and the demodulation result after further calibration is shown in Figure 7 (e), the root mean square error is further reduced by 1.5 μm. Compared with the traditional method, the channel calibration and noise compression technology makes the demodulation error of the radar for weak motion decrease by 6.6 μm in total, accounting for about 15.4% of the traditional method. The weak displacement motion becomes more obvious, and the accuracy of radar detection of displacement motion is improved.

[0033] Compared with the existing technology, the method improves the quadrature CW radar channel mismatch and noise, overcomes the problem that the amplitude and phase mismatch of the echo signal is difficult to calibrate when the radar detects weak motion, and improves the signal-to-noise ratio of the echo signal, finally improves the detection ability and detection precision of the quadrature radar for weak motion.

[0034] The above specific embodiments can be adjusted in different ways by those skilled in the art without departing from the principles and purposes of the present application, the protection scope of the present application is subject to the claims and is not limited by the above specific embodiments, each implementation scheme within the scope is subject to the present application.

Claims

1. An orthogonal CW radar weak motion optimization detection method, characterized in that: By pre-displacement motion and collecting the echo signals generated by the pre-motion, a reference ellipse is formed to extract the mismatch parameters caused by the channel mismatch of the orthogonal CW radar echo signal. The equivalent mathematical expectation of the radar echo signal generated by the weak moving target is calculated to achieve noise compression. The extracted mismatch parameters are then used to perform channel calibration on the echo signal after noise compression, thereby achieving the effect of accurately detecting weak motion. Radar channel mismatch parameter extraction: using radar to detect a displacement motion And store echo data and ,by is the horizontal axis, As the vertical coordinate, the data points are plotted in the two-dimensional phase diagram, a complete reference ellipse is formed by fitting, and the ellipse coefficient is extracted; finally, the amplitude mismatch parameter is calculated according to the ellipse equation and phase mismatch parameters ; Channel calibration includes: 1) Calculate the equivalent mathematical expectation: collect the data Divided into segments, each segment is , for The equivalent mathematical expectation of the fragments is ( ),Right now 、 ,in: , is the sampling frequency; 2) Calibrate channel mismatch: Use the estimated and right / Perform calibration where: It is the reference value and no further calibration is required. ; ,in: ； DC bias calibration: Using The characteristics of and Perform circle fitting and calculate the center of the circle and the radius of the circle , and finally obtain the normalized orthogonal echo signal and ,in: , ; Displacement demodulation: Using the inverse tangent function, the phase is extracted and the micro-motion trajectory contained in the phase is calculated, that is, .

2. The orthogonal CW radar weak motion optimization detection method according to claim 1, characterized in that: The pre-motion test means that before testing weak motion, a long displacement motion of a strongly reflective target is tested first, and the orthogonal echo signal generated by the target motion is recorded. Each radar system only needs to perform one pre-motion test.

3. The orthogonal CW radar weak motion optimization detection method according to claim 1, characterized in that: The reference ellipse refers to: a phase diagram is drawn with the radar orthogonal echo signals as the horizontal and vertical coordinates respectively. Due to the orthogonal signal amplitude mismatch and phase mismatch caused by channel mismatch, the phase diagram, which should be circular, appears as an ellipse. The arc length of the ellipse depends on the length of the target movement. If the pre-motion displacement is long enough, its echo signal can be fitted to form a complete ellipse. The complete ellipse can make the extraction of mismatch parameters more accurate.

4. The orthogonal CW radar weak motion optimization detection method according to claim 1, characterized in that: The mismatch parameter refers to: due to the imperfect phase shifter, power divider and mixer in the orthogonal radar system hardware, the echo signal channel mismatch is caused, so that the orthogonal echo signals that should have equal amplitudes and 90° phase difference do not meet the conditions in terms of amplitude and phase; the mismatch parameter includes the amplitude mismatch parameter , that is, the ratio of the amplitudes of the two orthogonal echo signals and the phase mismatch parameter , that is, the phase difference between the two echo signals minus 90°.

5. The orthogonal CW radar weak motion optimization detection method according to claim 1, characterized in that: The equivalent mathematical expectation calculation is to divide the collected echo signal into The data length is For each fragment The data points are averaged to obtain an equivalent data point, and we get data points to replace the original echo signal, where: , is the number of echo signal data points collected; according to the random signal analysis principle, for one-dimensional random signal , its mathematical expectation ,when When is a sufficiently large finite value, ; For determining the signal , the mathematical expectation represents the average value of the signal over the entire period of time, that is, , when the sampling rate is much greater than The rate of change over time, considered within a segment Almost unchanged, so And the mathematical expectation calculation satisfies linearity, .

6. The orthogonal CW radar weak motion optimization detection method according to claim 1, characterized in that: The channel calibration is to use the reference ellipse to calculate the radar system mismatch parameters and , calibrate the orthogonal echo signals to signals with equal amplitudes and a phase difference of 90°.

7. An orthogonal CW radar weak motion optimization detection system implementing the method according to any one of claims 1 to 6, characterized in that: include: Channel calibration and noise compression module, DC offset calibration module and phase demodulation module, among which: the channel calibration and noise compression module performs channel calibration processing according to the radar orthogonal channel mismatch parameters extracted by pre-motion, and at the same time uses the equivalent mathematical expectation of the echo signal to calculate the compressed additive noise to achieve the effect of compensating for the amplitude and phase distortion of the orthogonal echo signal and improve its signal-to-noise ratio. The DC offset calibration module uses the orthogonality of the echo signal to remove the DC offset voltage of the orthogonal echo signal and normalize the signal amplitude. The phase demodulation module performs phase decomposition calculation based on the relationship between the phase information of the echo signal and the target's weak motion, and finally extracts the target's weak motion.

8. The orthogonal CW radar weak motion optimization detection system according to claim 7, characterized in that: The orthogonal CW radar system includes: a transmitting antenna, a receiving antenna, a voltage-controlled oscillator (VCO), a power amplifier (PA), a low-noise amplifier (LNA), a down-conversion module, a baseband operational amplifier (Amp), and a data acquisition card (DAQ). The down-conversion module includes a 90-degree phase shifter and two mixers. The VCO generates a continuous sine wave signal with a fixed frequency and divides it into two paths. One path is sent to the down-conversion module as a local oscillator (LO) signal, and the other path is amplified by the power amplifier (PA) and then transmitted by the transmitting antenna. After the signal reaches the target to be measured, it is modulated by the target's weak motion and generates an echo. The receiving antenna receives the echo and sends it to the down-conversion module through a low-noise amplifier (LNA). In the down-conversion module, the echo signal is mixed with the original local oscillator signal and the local oscillator signal after 90° phase shift, and the mismatched orthogonal echo signal is output. and , and After DAQ data acquisition, the digital signal is obtained and ; The mismatched orthogonal echo signals include: , ,in: is the signal amplitude, and are the amplitude mismatch parameters and phase mismatch parameters of the orthogonal channel, is the orthogonal CW radar carrier wavelength, For weak target movement, is the DC bias, and is additive noise, which is usually defined as a zero-mean Gaussian random process, i.e. , is the residual phase noise; The digital signal , , where: To meet the calculation conditions of equivalent mathematical expectation, the sampling frequency Needs to be satisfied .

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