Frequency modulated continuous wave radar, digital signal processing method and characterization information detection method

Abstract

A digital signal processing method is provided to reduce the noise caused by environmental interference by superimposing the digital signals obtained by a receiving end receiving radar signals. Thus, the output signals obtained after superimposition can be used to measure the accurate characterization information of the detected target.

Description

TECHNICAL FIELD

[0001] The present application relates to radar signal processing technology, in particular, a frequency modulated continuous wave radar, a digital signal processing method and a characterization information detection method. BACKGROUND

[0002] Radar technology can be used in many outdoor field applications, such as speed measurement, distance measurement. However, in indoor fields, there are many environmental interference factors, causing inaccurate measurement results. For example: floor, wall, cabinet cause signal reflection interference, window curtain swing, fan rotation and other object movement will also cause signal disturbance. SUMMARY

[0003] Therefore, according to some embodiments, the frequency modulated continuous wave radar includes a transmitting unit and a receiving unit. The transmitting unit is used to send a plurality of chirp signals. The receiving unit receives the reflected chirp signals to generate a plurality of digital signals corresponding to the chirp signals. The receiving unit then superimposes the digital signals to obtain an output signal, and calculates the characterization information of the detected target according to the output signal.

[0004] According to some embodiments, the receiving unit superimposes the digital signals corresponding to the chirp signals in the same frame to obtain the output signal.

[0005] According to some embodiments, the receiving unit superimposes the digital signals corresponding to the chirp signals in the adjacent frames to obtain the output signal.

[0006] According to some embodiments, the receiving unit superimposes the digital signals corresponding to the chirp signals in the adjacent frames to obtain the output signal.

[0007] According to some embodiments, the transmitting unit includes at least one transmitting antenna. The receiving unit superimposes the digital signals corresponding to the chirp signals from the same transmitting antenna.

[0008] According to some embodiments, the receiving unit includes a plurality of receiving antennas. The receiving unit superimposes the digital signals corresponding to the chirp signals from the same transmitting antenna received by one of the receiving antennas to obtain the output signal.

[0009] According to some embodiments, the receiving unit includes a plurality of receiving antennas. The receiving unit superimposes the digital signals corresponding to the chirp signals from the same transmitting antenna received by one of the receiving antennas to obtain the output signal.

[0010] According to some embodiments, the transmitting unit includes a plurality of transmitting antennas. The receiving unit superimposes the digital signals corresponding to the chirp signals from at least two of the plurality of transmitting antennas.

[0011] According to some embodiments, the receiving unit comprises a plurality of receiving antennas. The receiving unit superimposes digital signals corresponding to chirp signals received by at least two of the plurality of transmitting antennas to obtain an output signal.

[0012] According to some embodiments, the receiving unit comprises a plurality of receiving antennas. The receiving unit superimposes digital signals corresponding to chirp signals received by at least two of the plurality of transmitting antennas to obtain an output signal.

[0013] According to some embodiments, the receiving unit further generates statistical information according to the output signal, and corrects the output signal according to the statistical information.

[0014] According to some embodiments, the statistical information is absolute sum, absolute maximum, standard deviation, or variance.

[0015] According to some embodiments, the receiving unit determines whether a detection target exists in a detection region according to the output signal and a machine learning model.

[0016] According to some embodiments, the receiving unit calculates representation information of the detection target according to the output signal when it is determined that the detection target exists.

[0017] According to some embodiments, the method of processing digital signals is performed by a processor in a signal processing device, comprising: superimposing a plurality of digital signals corresponding to a plurality of chirp signals received by a receiving end of a Doppler radar to obtain an output signal; and calculating representation information of a detection target according to the output signal.

[0018] According to some embodiments, the superimposed digital signals correspond to chirp signals in the same frame or in adjacent frames.

[0019] According to some embodiments, the method of processing digital signals further comprises: processing the digital signals to be superimposed before superimposing the digital signals.

[0020] According to some embodiments, the method of processing digital signals further comprises: generating statistical information according to the output signal; and correcting the output signal according to the statistical information.

[0021] According to some embodiments, the method of processing digital signals further comprises: determining whether a detection target exists in a detection region according to the output signal and a machine learning model.

[0022] According to some embodiments, the step of calculating representation information of a detection target according to the output signal is performed when it is determined that the detection target exists.

[0023] According to some embodiments, the characterization information detection method comprises: receiving a plurality of digital detection signals corresponding to the Doppler radar; performing frequency domain analysis on the digital detection signals to obtain a plurality of frequency domain detection signals; generating a plurality of statistical information according to the frequency domain detection signals; correcting the frequency domain detection signals according to the statistical information; determining whether a detection target exists in the detection region according to the corrected frequency domain detection signals and a machine learning model; and in response to the existence of the detection target, calculating the characterization information of the detection target according to the corrected frequency domain detection signals.

[0024] In summary, according to some embodiments, the frequency modulated continuous wave radar, the digital signal processing method and the characterization information detection method can solve the problem of poor signal caused by static and dynamic environmental interference, and can reduce the amount of data processing and speed up the processing speed. According to some embodiments, the frequency modulated continuous wave radar, the digital signal processing method and the characterization information detection method can identify whether a detection target exists or not, so as to improve the processing efficiency and filter false positives. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 A use state diagram of the frequency modulated continuous wave radar according to some embodiments;

[0026] Figure 2 A block diagram of the frequency modulated continuous wave radar according to some embodiments;

[0027] Figure 3 A diagram illustrating radar signals;

[0028] Figure 4 A detailed block diagram of the frequency modulated continuous wave radar according to some embodiments;

[0029] Figure 5 A diagram illustrating transmitted and received radar signals;

[0030] Figure 6 A signal processing diagram according to some embodiments;

[0031] Figure 7 A block diagram of a signal processing device according to some embodiments;

[0032] Figure 8 A flowchart of a digital signal processing method according to an embodiment;

[0033] Figure 9 A diagram illustrating signal superposition;

[0034] Figure 10 A diagram illustrating chirp signals;

[0035] Figure 11 A diagram illustrating received Figure 10schematic diagram of a signal;

[0036] Figure 12 schematic diagram of another example signal superposition;

[0037] Figure 13 schematic diagram of yet another example signal superposition;

[0038] Figure 14 schematic diagram of a digital signal after a range Fourier transform without signal superposition in a static environment;

[0039] Figure 15 schematic diagram of a digital signal after a range Fourier transform with signal superposition as shown in Figure 13

[0040] Figure 16 flowchart of a digital signal processing method according to another embodiment;

[0041] Figure 17 flowchart of calculating information of a detection target according to an embodiment;

[0042] Figure 18 schematic diagram of generation of statistical information;

[0043] Figures 19A-19E schematic diagram of frequency domain signals of different environmental disturbances;

[0044] Figures 20A-20E schematic diagram of corrected frequency domain signals of different environmental disturbances;

[0045] Figure 21A schematic diagram of frequency domain signals of a detection target lying on one side;

[0046] Figure 21B schematic diagram of corrected frequency domain signals of a detection target lying on one side;

[0047] Figure 22 flowchart of calculating information of a detection target according to another embodiment;

[0048] Figure 23 schematic diagram of a histogram when there is no detection target;

[0049] Figure 24 schematic diagram of a histogram when there is a detection target; and

[0050] Figure 25 flowchart of a characterization information detection method according to some embodiments. DETAILED DESCRIPTION

[0051] Reference is made to Figure 1 ​Fig. 1 is a usage state diagram of a frequency modulated continuous wave (FMCW) radar 10 according to some embodiments. The frequency modulated continuous wave radar 10 can detect a detection region 40. The detection result can be used to calculate one or more information of a detection target 50, such as distance, bearing, moving speed, physiological information (e.g. heartbeat, respiration), etc. The detection target 50 can be, for example but not limited to, a living body (e.g. a human body).

[0052] Referring to Figure 2 Fig. 2 is a block diagram of the frequency modulated continuous wave radar 10 according to some embodiments. The frequency modulated continuous wave radar 10 comprises a transmitting unit 20 and a receiving unit 30. The transmitting unit 20 transmits radar signals, and the receiving unit 30 receives reflected radar signals.

[0053] Referring to Figure 3 , Figure 3 Fig. 3 is a diagram illustrating radar signals. The upper half presents the amplitude of the radar signals against time, and the lower half presents the frequency of the radar signals against time. The radar signals transmitted by the transmitting unit 20 comprise a plurality of chirp signals SC. For the sake of clarity of the drawing, Figure 3 only one chirp signal SC is presented. Here, the chirp signal SC is a linear frequency pulse signal, which refers to a sinusoidal wave whose frequency increases linearly with time. In some embodiments, the frequency of the chirp signal SC increases in a non-linear manner. For the sake of convenience of explanation, the linear manner is used for explanation hereinafter. As shown in Figure 3 the chirp signal SC increases linearly from a starting frequency (e.g. 77 GHz) to an ending frequency (e.g. 81 GHz) according to a slope S within a time duration Tc (e.g. 40 microseconds). The starting frequency and the ending frequency can be selected from the millimeter wave band (i.e. 30 GHz to 300 GHz). The difference between the starting frequency and the ending frequency is the pulse bandwidth B.

[0054] Referring to Figure 4 and Figure 5 . Figure 4 Fig. 4 is a detailed block diagram of the frequency modulated continuous wave radar 10 according to some embodiments. Figure 5A schematic diagram illustrating the transmitted and received radar signals. The transmitting unit 20 comprises a transmitting antenna 22 and a radar transmitter 24. The radar transmitter 24 comprises a signal synthesizer for generating a chirp signal Ct and transmitting it via the transmitting antenna 22. The receiving unit 30 comprises a receiving antenna 32, a radar receiver 34 and a processing unit 36. The receiving antenna 32 receives the reflected radar signal (chirp signal Cr). The chirp signal Cr can be regarded as a delayed version of the chirp signal Ct. The radar receiver 34 comprises a mixer, a low pass filter and an analog-to-digital converter. The mixer couples the chirp signal Ct from the radar transmitter 24 and the received chirp signal Cr and can generate two coupled signals, the sum and the difference of the frequencies of the two chirp signals Ct, Cr. The low pass filter low pass filters the coupled signals to obtain the coupled signal of the difference of the frequencies of the two chirp signals Ct, Cr, hereinafter referred to as the “intermediate frequency signal SI”. The analog-to-digital converter converts the intermediate frequency signal SI into a digital signal for digital signal processing by the processing unit 36. The processing unit 36 can be, for example, a central processing unit (CPU), a graphics processing unit (GPU), or other programmable general purpose or special purpose microprocessors (Microprocessor), digital signal processors (Digital Signal Processor, DSP), programmable controllers, application specific integrated circuits (Application Specific Integrated Circuits, ASIC), programmable logic devices (Programmable Logic Device, PLD) or other similar devices, chips, integrated circuits and combinations thereof.

[0055] In another embodiment of the present disclosure, the frequency modulated continuous wave radar 10 further comprises a transmission module connected to the processing unit 36. The transmission module is configured to transmit the results of the digital signal processing by the processing unit 36 to an edge device or a cloud server at the other end.

[0056] In another embodiment of the present disclosure, the processing unit 36 of the frequency modulated continuous wave radar 10 only performs partial processing on the digital signal from the analog-to-digital converter, and the results of the partial processing are transmitted to an edge device or a cloud server at the other end by a transmission module of the frequency modulated continuous wave radar 10 for subsequent digital signal processing and operation.

[0057] In another embodiment of the present disclosure, the processing unit 36 of the frequency modulated continuous wave radar 10 does not perform any processing on the digital signals from the analog-to-digital converter, but directly transmits the digital signals from the analog-to-digital converter to an edge device or a cloud server at the other end through a transmission module of the frequency modulated continuous wave radar 10 for digital signal processing and operation.

[0058] With reference to Figure 5 The frequency f0of the intermediate frequency signal SI can be represented as Equation 1, S is the slope, and τ is the delay time between the radar signal transmission and reception. Therefore, τ can be represented as Equation 2, d is the distance between the transmitting antenna of the frequency modulated continuous wave radar 10 and the object to be detected, and c is the speed of light. Substituting Equation 2 into Equation 1 can obtain Equation 3. It can be known from Equation 3 that the frequency f0of the intermediate frequency signal SI implicitly contains distance information (i.e., the distance between the frequency modulated continuous wave radar 10 and the detection target 50).

[0059] f0= S · τ … Equation 1

[0060] τ = 2d / c … Equation 2

[0061] f0= 2Sd / c … Equation 3

[0062] With reference to Figure 6 which is a signal processing schematic diagram according to some embodiments. Here, the chirp signals SC are sequentially numbered as C1, C2, C3, …, Cn, n is a positive integer. The radar receiver 34 converts the received intermediate frequency signals SI corresponding to each chirp signal C1-Cn into digital signals SD (represented as D1, D2, …, Dn, n is a positive integer). The values of each digital signal SD can be represented as a one-dimensional array (row matrix). Sequentially arranging the plurality of row matrices vertically can become a two-dimensional array A1. It can be understood that the digital signals SD can also be arranged into column matrices and sequentially arranged horizontally, and a two-dimensional array can also be obtained. The values of the two-dimensional array A1 represent signal strength (amplitude). The index values of the columns of the two-dimensional array A1 correspond to the order of the chirp signals SC (digital signals SD). The index values of the rows of the two-dimensional array A1 have the meaning of time, that is, the row matrix of the two-dimensional array A1 is a time domain signal.

[0063] Processing unit 36 ​​performs a Fast Fourier Transform (FFT) (hereinafter referred to as "range Fourier Transform") on each column of the two-dimensional array A1 (i.e., the digital signal SD) to obtain the frequency domain signal SF (denoted as F1, F2, ..., Fn, where n is a positive integer), i.e., the two-dimensional array A2. Therefore, the columns of the two-dimensional array A2 are equivalent to a spectral distribution. As mentioned earlier, the frequency of the intermediate frequency signal SI implicitly contains range information. That is, the index values ​​of the columns of the two-dimensional array A2 have range meaning. The values ​​of the two-dimensional array A2 represent the intensity of each frequency in the spectrum, and can present the radar signal intensity reflected at different distances from the frequency-modulated continuous wave radar 10. Figure 6 As shown, the filled boxes in the two-dimensional array A2 represent peak values ​​(i.e., values ​​exceeding a threshold), indicating that an object is present at the distance corresponding to this frequency. The distance between the frequency-modulated continuous wave radar 10 and the detected target 50 can be calculated from the frequency at the peak value.

[0064] Because the intervals between each chirped signal SC are very short (e.g., tens of microseconds), the position of the same object reflecting the multiple chirped signals SC remains essentially unchanged. Therefore, each frequency domain signal SF has a filled box corresponding to the same distance, resulting in a linear filled box. For example... Figure 6 As shown, in this example, there are two vertical filled boxes. Although the frequency domain signals SF all have peaks in the same vertical row, subtle motion changes cannot be seen as significant changes in frequency; however, the phase component will have a significant impact. The vertical index values ​​of the two-dimensional array A2 correspond to the order of the frequency domain signals SF (chirped signals SC), which means they are in time order. Therefore, each vertical matrix of the two-dimensional array A2 can be regarded as a time domain signal. The processing unit 36 ​​performs a fast Fourier transform (hereinafter referred to as "Doppler Fourier transform") on each vertical matrix of the two-dimensional array A2, and can obtain the phase frequency domain signals SQ (represented as Q1, Q2, ..., Qm, where m is a positive integer), i.e., the two-dimensional array A3. Therefore, the vertical matrix of the two-dimensional array A3 is equivalent to the phase spectrum distribution. The phase φ0 of the intermediate frequency signal SI can be expressed as Equation 4, which, after substituting into Equation 2, can be expressed as Equation 5, where λ is the wavelength. Based on Equation 5, Equation 6 can be derived, where v is the velocity, Δφ is the phase difference between two adjacent chirped signals (Cn-1, Cn), and Δt is the time difference between two adjacent chirped signals SC. Equation 6 shows that the phase of the intermediate frequency signal SI implicitly contains motion information (velocity). Therefore, the index values ​​of the rows in the two-dimensional array A3 have velocity implications. From the phase-frequency domain signal SQ, the moving velocity or frequency of periodic motion of the detected target 50 can be calculated, thus obtaining characterization information of the detected target 50 (such as motion information, physiological information (such as respiratory rate, heart rate)). Figure 6For example, as shown in a two-dimensional array A3, there are two filled color boxes and three filled color boxes in two straight lines, indicating that there are at least two detected targets 50 at different distances from the frequency-modulated continuous wave radar 10, and the speed (frequency) corresponding to each filled color box is the characteristic information of the corresponding detected target 50.

[0065] φ0= 2πf0τ … Equation 4

[0066]

[0067]

[0068] In some embodiments, the processing unit 36 can not perform the fast Fourier transform on the entire two-dimensional array A2, but only perform the fast Fourier transform on the same peak of the frequency domain signal SF (here, two straight line matrices represented by filled color boxes) to reduce the amount of calculation and save calculation time.

[0069] As can be understood from the above description, by performing signal coupling, analog-to-digital conversion, and digital signal processing on the received chirp signal Cr, distance information and characteristic information can be obtained. However, in an indoor environment, radar signals are easily affected by other factors outside the detection area 40, causing information misjudgment. For example: static environmental interference caused by signal reflection on walls or floors, dynamic environmental interference caused by signal disturbance by other moving objects (such as electric fans, curtains). Therefore, after obtaining the digital signal SD, and before performing the aforementioned distance Fourier transform and Doppler Fourier transform and other signal processing, the following digital signal processing method can be performed to solve the problem of poor signal caused by environmental interference.

[0070] By reference to Figure 7 and Figure 8 . Figure 7 A block schematic diagram of a signal processing device 60 according to some embodiments. Figure 8A flowchart of a digital signal processing method according to an embodiment is shown. The signal processing device 60 includes a processor 61 and a storage device 62. The storage device 62 is a computer-readable storage medium for storing a program 63 for execution by the processor 61 to perform the digital signal processing method. In some embodiments, the signal processing device 60 is a Doppler radar (e.g., the frequency-modulated continuous wave radar 10), and the processor 61 is the processing unit 36. In some embodiments, the Doppler radar is a continuous wave (CW) radar or an ultra-wideband (UWB) radar. In some embodiments, the signal processing device 60 is an edge device or a cloud server, i.e., the digital signal SD obtained by the frequency-modulated continuous wave radar 10 is transmitted to the edge device or the cloud server for digital signal processing.

[0071] By way of example Figures 7-9 , Figure 9 A schematic diagram illustrating signal stacking is shown. The received intermediate frequency signals SI corresponding to the chirp signals C1-Cn are converted into digital signals P1-Pn. In step S200, the digital signals SP corresponding to the chirp signals SC are stacked to obtain an output signal SE (e.g., E1-Ek, where k is a positive integer) as shown in FIG. 2B. Figure 9 In the example shown in FIG. 2B, every two adjacent digital signals SP are stacked to obtain the output signal SE. For example, the digital signals P1 and P2 are stacked to obtain the output signal E1, and the digital signals P3 and P4 are stacked to obtain the output signal E2. By stacking the signals, random noise caused by the environment can be averaged, and the signal-to-noise ratio (SNR) can be improved. In addition, after stacking the signals, multiple one-dimensional arrays can be combined into one one-dimensional array, and the data processing amount can be greatly reduced, and the processing speed can be increased. Here, although the stacking of two adjacent digital signals SP is used as an example, the embodiments of the present application are not limited thereto, and more than two adjacent digital signals SP can be stacked.

[0072] In some embodiments, the digital signals SP stacked with each other correspond to multiple chirp signals SC in the same frame. In other embodiments, the digital signals SP stacked with each other correspond to multiple chirp signals SC in multiple adjacent frames. The multiple adjacent frames can be more than two frames.

[0073] In step S300, the distance Fourier transform and the Doppler Fourier transform described above can be performed on the output signal SE to calculate the distance information and the characteristic information (motion information and physiological information) of the detection target 50. ​

[0074] The foregoing description has been given with reference to the case where the transmission unit 20 has one transmission antenna 22 and the reception unit 30 has one reception antenna 32. However, in some embodiments, the transmission unit 20 can have a plurality of transmission antennas 22. Similarly, in some embodiments, the reception unit 30 can have a plurality of reception antennas 32.

[0075] Referring to Figure 10 , which is a diagram illustrating the reception of the chirp signals SC. Here, the case where the transmission unit 20 has two transmission antennas 22 is described. Here, the chirp signals SC are denoted as Tx1 and Tx2, respectively, indicating the chirp signals SC transmitted from the first transmission antenna 22 and the second transmission antenna 22, respectively. The radar signals are defined by a plurality of frames M (denoted as M1 to Mp, p being a positive integer). Each frame M includes a plurality of chirp signals SC. Here, the case where the respective transmission antennas 22 transmit the chirp signals Tx1 and Tx2 alternately, a total of four chirp signals SC, is described. The period of a frame M can be, for example, 20 milliseconds. During each frame M, the processor 61 performs the aforementioned digital signal processing method in accordance with the chirp signals SC in each frame M. That is, the processor 61 superimposes the digital signals SP corresponding to the chirp signals SC in the same frame M to obtain an output signal SE, and performs the process S300. For example, during the frame M1, the digital signal processing method is performed once in accordance with the two chirp signals Tx1 and the two chirp signals Tx2 in the frame M1; during the frame M2, the digital signal processing method is performed once in accordance with the two chirp signals Tx1 and the two chirp signals Tx2 in the frame M2. The different signal superimposition methods are described below.

[0076] Referring to Figure 11 , which is a diagram illustrating the reception Figure 10 of the radar signals. Here, the case where the reception unit 30 having four reception antennas Rx1, Rx2, Rx3, and Rx4 receives the radar signals shown in Figure 10 is described. The chirp signals Tx1 and Tx2 are received by the respective reception antennas Rx1, Rx2, Rx3, and Rx4, and converted into digital signals SP (here, only four digital signals P1 to P4 of one frame M are described) by the radar receiver 34. The first digital signal P1 corresponds to the first chirp signal Tx1 transmitted by the first transmission antenna 22; the second digital signal P2 corresponds to the first chirp signal Tx2 transmitted by the second transmission antenna 22; the third digital signal P3 corresponds to the second chirp signal Tx1 transmitted by the first transmission antenna 22; and the fourth digital signal P4 corresponds to the second chirp signal Tx2 transmitted by the second transmission antenna 22.

[0077] Referring to Figure 12This is another schematic diagram illustrating signal superposition. The processor 61 can superimpose the digital signals SP corresponding to the chirped signals SC received by each receiving antenna Rx1 to Rx4 from the same transmitting antenna 22. For example, the first digital signal P1 and the third digital signal P3 both correspond to the chirped signal Tx1 from the first transmitting antenna 22, and they are superimposed to form the superimposed signal SG (denoted as G1 to G4 respectively). The processor 61 further superimposes the signals (G1 to G4) corresponding to each receiving antenna Rx1 to Rx4 in the superimposed signal SG to obtain the output signal SE. That is, the processor 61 superimposes the digital signals SP corresponding to the chirped signals SC received by the receiving antennas Rx1 to Rx4 from the same transmitting antenna 22 to obtain the output signal SE. In some embodiments, the processor 61 superimposes the digital signals SP corresponding to the chirped signals SC from other transmitting antennas 22 (such as the chirped signal Tx2 from the second transmitting antenna 22).

[0078] In some embodiments, the processor 61 does not superimpose the superimposed signals SG corresponding to each receiving antenna Rx1 to Rx4, but instead selects the superimposed signal G1, G2, G3, or G4 corresponding to one of the receiving antennas Rx1 to Rx4 as the output signal SE. That is, the output signal SE is obtained by superimposing the digital signal SP corresponding to the chirped signal SC received from the same transmitting antenna 22 by one of the plurality of receiving antennas Rx1 to Rx4.

[0079] Reference Figure 13 This is yet another schematic diagram illustrating signal superposition. It differs from... Figure 12 The processor 61 superimposes only the digital signal SP corresponding to the chirp signal SC from the same transmitting antenna 22. The processor 61 can also superimpose the digital signals SP corresponding to the chirp signals SC from different transmitting antennas 22 (i.e., at least two transmitting antennas 22). For example, although digital signals P1 to P4 come from different transmitting antennas 22, the processor 61 superimposes the digital signals P1 to P4 corresponding to the chirp signals SC received by each receiving antenna Rx1 to Rx4 to form a superimposed signal SG (denoted as G1 to G4 respectively). The processor 61 further superimposes the signals (G1 to G4) corresponding to each receiving antenna Rx1 to Rx4 in the superimposed signal SG to obtain the output signal SE. In other words, the processor 61 superimposes the digital signals SP corresponding to the chirp signals SC received by receiving antennas Rx1 to Rx4 from different transmitting antennas 22 (i.e., at least two transmitting antennas 22) to obtain the output signal SE.

[0080] Reference Figure 14 and Figure 15 . Figure 14Fig. 4 is a schematic diagram illustrating the distance Fourier transform of the digital signals SP without signal superposition in a static environment. Figure 15 Fig. 5 is a schematic diagram illustrating the distance Fourier transform of the digital signals SP with signal superposition in a static environment. Figure 13 Fig. 5 is a schematic diagram illustrating the distance Fourier transform of the digital signals SP with signal superposition in a static environment.

[0081] In some embodiments, the processor 61 does not superimpose the superimposed signals SG corresponding to each receiving antenna Rx1-Rx4, but selects the superimposed signal G1, G2, G3 or G4 corresponding to one of the receiving antennas Rx1-Rx4 as the output signal SE. That is, the digital signals SP corresponding to the chirp signals SC from different transmitting antennas 22 (i.e. at least two transmitting antennas 22) received by one of the receiving antennas Rx1-Rx4 are superimposed to obtain the output signal SE.

[0082] In some embodiments, although the foregoing is described with respect to superimposing the chirp signals SC in the same frame M, the processor 61 can superimpose the digital signals SP corresponding to the chirp signals SC in adjacent frames M to obtain the output signal SE. In some embodiments, the processor 61 can superimpose the digital signals SP corresponding to the chirp signals SC in at least three adjacent frames M to obtain the output signal SE. As described above, the manner of superimposing the digital signals SP in at least two adjacent frames M can be superimposing the digital signals SP corresponding to the chirp signals SC from the same transmitting antenna 22, or superimposing the digital signals SP corresponding to the chirp signals SC from different transmitting antennas 22, which will not be repeated here. As described above, one of the superimposed signals (superimposed signals SG) can be selected as the output signal SE, or the superimposed signals SG can be superimposed to obtain the output signal SE, which will not be repeated here. Here, since the digital signals SP corresponding to the chirp signals SC in at least two adjacent frames M are superimposed, the digital signal processing method is performed once per at least two frames M.

[0083] Fig. 6 is a flowchart of a digital signal processing method according to another embodiment. Figure 16 Figure 8 ​The difference is that, before the flow S200, the flow S100 is performed first to superimpose the digital signals SP. Thus, the phase delay between the digital signals SP can be corrected. In some embodiments, if the phase delay between the digital signals SP to be superimposed is within the allowable range, the flow S100 can not be performed. For example, if the processor 61 is to superimpose the chirp signals SC in the same frame M, the phase delay is generally within the allowable range, and the flow S100 can not be performed. If the processor 61 is to superimpose the chirp signals SC in at least two adjacent frames M, and the phase delay exceeds the allowable range, the flow S100 is performed first before the flow S200.

[0084] With reference to Figure 17 which is a flowchart of calculating information of a detection target according to an embodiment. The flow S300 includes the aforementioned range Fourier transform (step S310), Doppler Fourier transform (step S370), and calculating information of the detection target 50 (step S390), and further includes steps S330 and S350.

[0085] With reference to Figure 17 and Figure 18 , Figure 18 is a schematic diagram illustrating the generation of statistical information. After obtaining the frequency domain signal SF (the horizontal axis is the range information after the range Fourier transform, the vertical axis is the signal intensity, and the vertical axis is the time, which is equivalent to a two-dimensional array A2 as shown in Figure 6 after the aforementioned step S310, the step S330 is entered. In the step S330, the processor 61 can first generate statistical information SV from the frequency domain signal SF. Specifically, the statistical information SV is calculated for the frequency domain signal SF according to the time axis. Through the statistical information SV, the signal characteristics can be analyzed to facilitate the distinction between dynamic interference and target signal sources in the environment. The statistical information SV can be, for example, the absolute sum of squares, the absolute maximum value, the standard deviation (Standard Deviation), or the variance (Variance). Specifically, the processor 61 calculates the statistical information SV for each column matrix CL of the two-dimensional array A2, that is, for the time series signal intensity of each distance. For example, a standard deviation p is calculated for each column matrix CL. As shown in Figure 18 , a distribution curve W is shown according to the plurality of standard deviations p, which can be used as a shield for the subsequent step S350 to correct the signal.

[0086] In step S350, the processor 61 corrects the signal according to the statistical information SV. That is, the frequency domain signal SF is normalized according to the statistical information SV. For example, the signal on the time series for each distance is multiplied by the corresponding statistical information SV (such as the standard deviation p), that is, each column matrix CL of the two-dimensional array A2 is respectively multiplied by the statistical information SV (such as the standard deviation p) corresponding to each column matrix CL. As shown in FIG. 6, it shows the corrected frequency domain signal SF'. Thereafter, more accurate distance information of the detection target 50, information representing information (such as motion information, physiological information) and the like can be calculated according to the corrected frequency domain signal SF' (step S390). Figure 18

[0087] By reference Figures 19A-19E and Figures 20A-20E . Figures 19A-19E FIG. 5 is a schematic diagram illustrating the frequency domain signal SF of the fan rotating without shaking the head. Figures 20A-20E FIG. 6 is a schematic diagram illustrating the corrected frequency domain signal SF' of the fan rotating without shaking the head. Figure 19A and Figure 20A is the environmental interference of the fan rotating without shaking the head. Figure 19B and Figure 20B is the environmental interference of the fan rotating with shaking the head. Figure 19C and Figure 20C is the environmental interference of the curtain being static. Figure 19D and Figure 20D is the environmental interference of the curtain shaking. Figure 19E and Figure 20E is the environmental interference of the other person moving. It can be clearly seen that through the aforementioned signal correction, the dynamic environmental interference can be indeed eliminated.

[0088] By reference Figure 21A and Figure 21B . Figure 21A FIG. 7 is a schematic diagram illustrating the frequency domain signal SF of the detection target 50 lying on one side. Figure 21B FIG. 8 is a schematic diagram illustrating the corrected frequency domain signal SF' of the detection target 50 lying on one side. Through the aforementioned signal correction, the bed reflection signal interference caused by different postures (such as lying on one side) of the detection target 50 can also be eliminated, and thus the influence caused by different sleeping postures is also well inhibited.

[0089] By reference Figure 7 and Figure 22 . Figure 22 ​This is a flowchart illustrating the calculation of information about the detected target according to another embodiment. The storage device 62 also stores a machine learning model 64, trained using the aforementioned corrected signals obtained under different conditions. These different conditions include: when the detected target 50 is present in the detection area 40 under various environmental conditions (such as the aforementioned fan rotation, curtain swaying, etc.); and when the detected target 50 is not present in the detection area 40 under various environmental conditions (such as the aforementioned fan rotation, curtain swaying, etc.). Figure 22 and Figure 17 The difference lies in the inclusion of step S360, which uses machine learning model 64 to determine whether a detection target 50 exists in the detection area 40 based on the corrected signal. If the detection target 50 exists, steps S370 and S390 are performed to calculate the distance information and representation information (such as motion information and physiological information) of the detection target 50; otherwise, the process ends. Through machine learning technology, features indicating the presence or absence of the detection target 50 can be learned to determine its existence. Therefore, in addition to saving computational resources when the detection target 50 is not present, it can also filter out false positives (e.g., avoiding the situation where representation information is calculated even when the detection target 50 is not present).

[0090] In some embodiments, when training the machine learning model 64 and using it for judgment, the modified signal can be pre-processed for feature acquisition before the acquired features are input into the machine learning model 64. The feature acquisition process can include statistical histograms, calculating the mean, standard deviation, variance, skewness, kurtosis, etc. Taking a statistical histogram as an example, the two-dimensional array A2 of the modified frequency domain signal SF' can be normalized, and the number of elements in each signal intensity interval can be counted based on the normalized values. (See also: Combined Reference) Figure 23 and Figure 24 As shown, histograms are illustrated for the absence of detection target 50 and the presence of detection target 50. Taking the division into 10 signal intensity intervals as an example, it can be seen that the histograms for the two cases have different distributions.

[0091] Reference Figure 25which is a flowchart of a characterization information detection method according to some embodiments. The characterization information detection method can be performed by the processor 61 of the aforementioned signal processing device 60. In step S410, a plurality of digital detection signals (i.e., the aforementioned digital signals SP) corresponding to the Doppler radar are received. In step S420, frequency domain analysis is performed on the digital detection signals to obtain a plurality of frequency domain detection signals (i.e., the aforementioned frequency domain signals SF). In step S430, a plurality of statistical information (i.e., the aforementioned statistical information SV) is generated according to the frequency domain detection signals. In step S440, the frequency domain detection signals are corrected according to the statistical information SV. Specifically, step S440 normalizes the frequency domain detection signals according to the statistical information SV. The statistical information SV is the absolute sum, the absolute maximum value, the standard deviation, or the variance of the frequency domain detection signals corresponding to a statistical period. In step S450, it is determined whether there is a detection target 50 in the detection region 40 according to the corrected frequency domain detection signals (i.e., the aforementioned corrected frequency domain signals SF’) and the machine learning model 64. In step S460, in response to the presence of the detection target 50, the characterization information of the detection target 50 is calculated according to the corrected frequency domain detection signals SF’. The related descriptions of each step have been described in detail above and will not be repeated here.

[0092] In some embodiments, the machine learning model 64 is stored in an edge device or a cloud server, and the frequency modulated continuous wave radar 10 transmits the aforementioned acquired features to the edge device or the cloud server through a transmission module thereof for subsequent machine model training or detection determination. Alternatively, the frequency modulated continuous wave radar 10 transmits the aforementioned corrected signals to the edge device or the cloud server through a transmission module thereof for subsequent digital signal processing, machine model training, and / or detection determination.

[0093] In summary, the frequency modulated continuous wave radar and the digital signal processing method according to some embodiments can solve the problem of poor signals caused by static and dynamic environmental interference, and can reduce the amount of data processing and speed up the processing speed. The frequency modulated continuous wave radar and the digital signal processing method according to some embodiments can identify the presence or absence of the detection target 50 to improve processing efficiency and filter false positives.

[0094] [Symbol Description]

[0095] 10: frequency modulated continuous wave radar

[0096] 20: transmitting unit

[0097] 22: transmitting antenna

[0098] 24: radar transmitter

[0099] 30: receiving unit

[0100] 32: reception antenna

[0101] 34: radar receiver

[0102] 36: processing unit

[0103] 40: detection area

[0104] 50: detection object

[0105] 60: signal processing device

[0106] 61: processor

[0107] 62: storage device

[0108] 63: program

[0109] 64: machine learning model

[0110] M, M1, M2, Mp: frame

[0111] A1, A2, A3: two-dimensional array

[0112] B: pulse bandwidth

[0113] CL: straight-ahead matrix

[0114] Ct, Cr: chirp signal

[0115] C1, C2, C3, Cn: chirp signal

[0116] D1, D2, D3, D4, Dn: digital signal

[0117] d: transmission distance

[0118] E1, E2, Ek: output signal

[0119] F1, F2, Fn: frequency domain signal

[0120] G1, G2, G3, G4: superimposed signal

[0121] Rx1, Rx2, Rx3, Rx4: reception antenna

[0122] P1, P2, P3, P4, Pn: digital signal

[0123] p: standard deviation

[0124] Q1, Q2, Qm: phase frequency domain signal

[0125] S: slope

[0126] SC: chirp signal

[0127] SD: digital signal

[0128] SE: output signal

[0129] SG: superimposed signal

[0130] SI: intermediate frequency signal

[0131] SP: digital signal

[0132] SF, SF': frequency domain signal

[0133] SQ: phase frequency domain signal

[0134] SV: statistical information

[0135] W: distribution curve

[0136] S100: digital signal to be superimposed

[0137] S200: output signal resulting from superimposing the chirp signal on the digital signal

[0138] S300: calculating information of the detection target from the output signal

[0139] S310: range Fourier transform

[0140] S330: generating statistical information

[0141] S350: correcting the signal from the statistical information

[0142] S360: determining whether a detection target is present in the detection region based on the machine learning model

[0143] S370: Doppler Fourier transform

[0144] S390: calculating information of the detection target

[0145] S410: receiving a plurality of digital detection signals corresponding to the Doppler radar

[0146] S420: performing frequency domain analysis on the digital detection signals to obtain a plurality of frequency domain detection signals

[0147] S430: generating a plurality of statistical information from the frequency domain detection signals

[0148] S440: correcting the frequency domain detection signals from the statistical information

[0149] S450: determining whether a detection target is present in the detection region based on the corrected frequency domain detection signals and the machine learning model

[0150] S460: calculating the characterization information of the detection target from the corrected frequency domain detection signals in response to the detection target being present

[0151] Tx1, Tx2: chirped signals

[0152] Tc: duration

[0153] τ: delay time

Claims

1. A frequency modulated continuous wave radar comprising: a transmitting unit that transmits a plurality of chirp signals; and a receiving unit that receives reflected said plurality of chirp signals, generates a plurality of digital signals corresponding to said plurality of chirp signals, superimposes said plurality of digital signals to obtain an output signal, and calculates a moving speed of a detected target or a frequency of a periodic motion of the detected target by performing a Doppler Fourier transform based on the output signal to obtain motion information or physiological information of the detected target; wherein the receiving unit further performs a range Fourier transform on a plurality of said output signals to obtain a plurality of frequency domain detection signals; arranges said plurality of frequency domain detection signals into a two-dimensional array, each column of the two-dimensional array comprising one of said plurality of frequency domain detection signals; generates statistical information by calculating a statistical value of each row of the two-dimensional array; and normalizes said plurality of frequency domain detection signals based on the statistical information.

2. The frequency modulated continuous wave radar of claim 1, wherein the receiving unit superimposes said plurality of digital signals corresponding to said plurality of chirp signals in a same frame to obtain the output signal.

3. The frequency modulated continuous wave radar of claim 1, wherein the receiving unit superimposes said plurality of digital signals corresponding to said plurality of chirp signals in adjacent frames to obtain the output signal.

4. The frequency modulated continuous wave radar of claim 3, wherein the receiving unit performs a bit alignment on said plurality of digital signals before superimposing them.

5. The frequency modulated continuous wave radar of claim 1, wherein the transmitting unit comprises at least one transmitting antenna, and the receiving unit superimposes said plurality of digital signals corresponding to said plurality of chirp signals from a same said transmitting antenna.

6. The frequency modulated continuous wave radar of claim 5, wherein the receiving unit comprises a plurality of receiving antennas, and the receiving unit superimposes said plurality of digital signals corresponding to said plurality of chirp signals from a same said transmitting antenna received by one of the receiving antennas to obtain the output signal.

7. The frequency modulated continuous wave radar of claim 5, wherein the receiving unit comprises a plurality of receiving antennas, and the receiving unit superimposes said plurality of digital signals corresponding to said plurality of chirp signals from a same said transmitting antenna received by said plurality of receiving antennas to obtain the output signal.

8. The frequency modulated continuous wave radar of claim 1, wherein the transmitting unit comprises a plurality of transmitting antennas, and the receiving unit superimposes said plurality of digital signals corresponding to said plurality of chirp signals from at least two of the transmitting antennas.

9. The frequency modulated continuous wave radar of claim 8, wherein the receiving unit comprises a plurality of receiving antennas, and the receiving unit superimposes said plurality of digital signals corresponding to said plurality of chirp signals from at least two of the transmitting antennas received by one of the receiving antennas to obtain the output signal. ​ 10. The frequency-modulated continuous wave radar of claim 8, wherein the receiving unit comprises a plurality of receiving antennas, and the receiving unit superimposes the plurality of digital signals corresponding to the plurality of chirp signals received by the plurality of receiving antennas from at least two of the plurality of transmitting antennas to obtain the output signal.

11. The frequency-modulated continuous wave radar of any one of claims 1 to 10, wherein the receiving unit further generates a statistical information according to the output signal, and normalizes the output signal according to the statistical information.

12. The frequency-modulated continuous wave radar of claim 11, wherein the statistical information is an absolute sum, an absolute maximum, a standard deviation, or a variance.

13. The frequency-modulated continuous wave radar of claim 11, wherein the receiving unit determines whether a detection target exists in a detection region according to the normalized output signal and a machine learning model.

14. The frequency-modulated continuous wave radar of claim 13, wherein when the receiving unit determines that the detection target exists, the receiving unit calculates a moving speed or a frequency of a periodic motion of the detection target by performing a Doppler Fourier transform according to the normalized output signal to obtain motion information or physiological information of the detection target.

15. A digital signal processing method performed by a processor in a signal processing device, comprising: superimposing a plurality of digital signals corresponding to a plurality of chirp signals received by a receiving end of a Doppler radar to obtain an output signal; and calculating a moving speed or a frequency of a periodic motion of a detection target by performing a Doppler Fourier transform according to the output signal to obtain motion information or physiological information of the detection target; wherein the step of calculating a moving speed or a frequency of a periodic motion of a detection target further comprises: performing a range Fourier transform on a plurality of the output signals to obtain a plurality of frequency-domain detection signals; arranging the plurality of frequency-domain detection signals into a two-dimensional array, each column of the two-dimensional array comprising one of the plurality of frequency-domain detection signals; generating a statistical information by calculating a statistical value of each row of the two-dimensional array; and normalizing the plurality of frequency-domain detection signals according to the statistical information.

16. The digital signal processing method of claim 15, wherein the plurality of digital signals corresponding to the plurality of chirp signals superimposed are in a same frame or in adjacent frames.

17. The digital signal processing method of claim 15, wherein before the step of superimposing the plurality of digital signals corresponding to the plurality of chirp signals received by the receiving end of the Doppler radar to obtain the output signal, the method further comprises: preprocessing the plurality of digital signals to be superimposed.

18. The digital signal processing method of claim 15, further comprising: generating a statistical information according to the output signal; and normalizing the output signal according to the statistical information.

19. The digital signal processing method of claim 15, further comprising: determining whether a detection target exists in a detection region according to the output signal and a machine learning model.

20. The digital signal processing method of claim 18, further comprising: ​ ​ A detection target is determined to exist in a detection region according to the normalized output signal and a machine learning model.

21. The digital signal processing method of claim 20, wherein the step of calculating the moving speed or the frequency of periodic motion of the detection target by performing a Doppler Fourier transform according to the normalized output signal is performed when the detection target is determined to exist.

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