Low altitude flying helicopter advanced detection method based on acoustic shock coupling

Abstract

The present application relates to a kind of low altitude flying helicopter advanced detection method based on acoustic shock coupling.For key area, low altitude flying helicopter becomes main invasion target, the present application is based on acoustic shock coupling principle, propose to use advanced seismic wave to low altitude flying helicopter is detected.First, reasonably arrange seismic detector array, through calibration time delay to the whole array signal is added and is pressed noise.Then, through advanced wave Doppler frequency shift formula and corresponding numerical relationship to obtain the frequency band interval of advanced wave and then band-pass filter noise.Again, using cross-correlation detection method to detect multiple groups of array corresponding advanced wave, according to the characteristics of advanced wave excited by helicopter design to time pickup algorithm.Through simulation data analysis, compared with acoustic wave detection technology, the present application can detect the arrival of helicopter earlier, has obvious advantage.

Description

Technical fields:

[0001] This invention relates to the field of low-altitude helicopter detection applications. This invention provides a novel sensing method for this field with a detection time earlier than acoustic detection technology, and in particular, it relates to an advanced detection method for low-altitude helicopters based on acoustic-vibration coupling. Background technology:

[0002] In key protected areas, such as border lines, power plants, oil transmission lines, highway intersections, and communication facilities, 24 / 7 surveillance is required to prevent enemy intrusion and damage. Low-flying helicopters are a primary target for intrusion. Currently, acoustic detection technology is mainly used to monitor the acoustic signals generated by helicopters. Compared to radar, visual recognition, and infrared technologies, this method has advantages such as no low-altitude blind spots, all-weather monitoring, and immunity to light source interference. Acoustic detection technology can identify intrusion targets as early as possible before low-flying helicopters arrive, buying more time for rear-area response. However, due to the high speed of these targets, acoustic detection technology has drawbacks such as short warning time, signal obstruction by large objects like buildings, and susceptibility to adverse weather conditions.

[0003] In fact, based on the principle of acoustic-vibration coupling, sound waves generated by low-flying targets can couple into the ground to form leading waves. Theoretically, these can propagate underground at speeds greater than 3-10 times the speed of sound, thus being detected earlier. Therefore, detecting leading waves holds promise for earlier detection of low-flying helicopters, which is of great significance for border security and combating illegal smuggling. Currently, several international studies have proven the existence of leading waves. However, the leading waves in these studies are intuitively clear in the time domain, while this invention addresses the application context of long-distance propagation of helicopter-generated leading waves, which are often submerged in noise and difficult to observe. Furthermore, the difficulty in using leading waves to detect low-flying targets lies in the lack of understanding of their characteristics. When leading waves are submerged in noise in the time domain, they cannot be detected based on their features. Therefore, there is an urgent need for a method that can use leading waves to detect low-flying helicopters in advance based on their characteristics. Summary of the Invention:

[0004] The purpose of this invention is to address the shortcomings of the prior art by providing a method for advanced detection of low-altitude helicopters based on acoustic-vibration coupling.

[0005] The inventive concept of this invention is as follows: First, based on the principle of acoustic-seismic coupling, sound waves generated by low-altitude sound sources can couple into the ground to form leading waves, which theoretically can propagate underground at speeds greater than 3-10 times the speed of sound and thus be detected earlier. Second, since leading waves are submerged in environmental noise in real-world environments, noise suppression is achieved by superimposing signals through array elements. Considering the single-frequency characteristics of seismic signals generated by helicopters, the frequency characteristics of leading waves are derived based on the Doppler frequency shift formula, and a filtering band and a leading wave arrival time acquisition algorithm are designed accordingly. Finally, the reliability of the arrival time results is analyzed by examining the slope of the leading wave arrival results from different array groups.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] 1. A method for advanced detection of low-altitude helicopters based on acoustic-vibration coupling, characterized by comprising the following steps:

[0008] a. Analyze the background noise of the deployment site, select a relatively quiet site, bury the seismic detector underground at a depth of not less than 0.3m, and collect a seismic background noise for at least 5 minutes. The average particle vibration velocity of the seismic background noise should not exceed 0.4μm / s. Otherwise, the detector needs to be buried deeper or the deployment site needs to be changed.

[0009] b. Deploy a seismic detector array, consisting of J arrays with an array spacing of no less than 500 meters. Each array shall contain no less than 10 array elements (seismic detectors) with a sensitivity of no less than 2 cm / s / V. The array element spacing shall be greater than the correlation radius of the random noise at the deployment site, so that the correlation coefficient between the seismic background noise received by each array element does not exceed 0.2.

[0010] c. For the superimposed and denoised seismic signal, after acquiring the helicopter seismic signal, for the j-th array group, calculate the relative time delay between the signal with the highest signal-to-noise ratio among the array elements and the signals of other array elements. Then, sum all the array element signals in the j-th array group after calibrating the time delay to obtain the superimposed and denoised seismic signal S. j (n), j = 1, 2, ..., J, n is the sampling point number, n = 1, 2, ..., N, N is the sampling length, and the sampling frequency is Fs, in Hz;

[0011] d. Analyze the frequency of the leading wave excited by the helicopter, and obtain the underground P-wave and S-wave velocities V at the array deployment site by consulting regional geological data and other methods. p and V s The helicopter's flight speed V is obtained through radar or other sensing technologies. f Find |S j The sampling point number n0 corresponding to the maximum amplitude in the signal (n)| is then calculated to obtain S. j(n) The frequency F0 corresponding to n0 in the time-frequency diagram is used to calculate the frequency values ​​of the leading P-wave and leading S-wave using the leading wave Doppler frequency shift formula.

[0012] f wp =V p F0 / (V p -V f ), f ws =V s F0 / (V s -V f (1)

[0013] e. Determine the frequency range of the leading wave, let A j It is S j The earliest arriving signal in (n), A j Find A, which arrives earliest in the time-frequency domain and whose frequency value does not change over time. j frequency F C f wp and f ws It also satisfies the following relationship

[0014] F0 < f wp <f ws <F C (2)

[0015] Formula (2) is f for step d. wp and f ws The results further confirm that the frequency of the lead wave is more reliable, and the frequency range of the lead wave is [f]. wp -W,f ws +W], where W is A j F in the spectrum C Half the width of a spectral peak;

[0016] f. S j (n) in [f wp -W,f ws After bandpass filtering of the +W frequency band, B is obtained. j (n), select the A1 portion of B1(n) and combine it with B j (n) Perform cross-correlation detection to obtain C j (n);

[0017] g. Time-of-arrival pickup of leading waves

[0018] |C j (n)| 2 >mean(|C j (n)| 2 )+X1·std(|C j (n)| 2 (3)

[0019] Where X1 is the weight parameter at time, "·" indicates multiplication, mean() is the function to calculate the average of the one-dimensional array within the parentheses, std() is the function to calculate the standard deviation of the one-dimensional array within the parentheses, and the first value of n that satisfies formula (3) is denoted as n. j n j / Fs is the arrival time of the leading wave (i.e., the detection time) corresponding to the j-th group, in seconds. Then, the arrival time of the leading wave for all arrays is calculated.

[0020] h. Determine the reliability of the detection timing. Let E(j) be the detection result of all array groups, and diff(E(j)) be the derivative of E(j).

[0021] |diff(E(j))| 2 >mean(|diff(E(j))| 2 )+X2·std(|diff(E(j))| 2 (4)

[0022] Where X2 is the reliability weight parameter, the minimum value of j that satisfies formula (4) is denoted as j0, then the detection results of the first j0 groups in E(j) are all reliable.

[0023] Beneficial effects:

[0024] This invention utilizes advanced seismic waves to detect the arrival of low-flying helicopters, which is beneficial for protecting key areas. The detection time obtained by this method is earlier than that of acoustic detection methods, allowing rear defense systems more preparation time. Furthermore, this method also has important reference value for other applications, such as maintaining traffic order at helicopter airports. Attached image description:

[0025] Figure 1 The time-distance plots of the cross-correlation results corresponding to the 30 arrays obtained by the method of the present invention show that the portion between the arrival time curves of the P-wave and the direct arrival wave is the detected leading wave.

[0026] Figure 2 According to the method of the present invention, the time when the leading wave of the 30 arrays arrives earlier than the time when the sound wave arrives is earlier than the time when the sound wave arrives. In the figure, the result corresponding to the method of the present invention is only meaningful if it is both less than the line corresponding to the P wave and greater than 0.

[0027] The following detailed description of the acoustic-vibration coupling-based advanced detection method for low-altitude helicopters proposed in this invention, with reference to the accompanying drawings and embodiments, will be provided in further detail.

[0028] This embodiment simulates a 30-array system, with the arrays spaced 0.5 km apart in a straight line. Each array contains 50 elements, and the horizontal distance between the first array and the helicopter's starting position is 0.5 km. Vp = 1400 m / s, Vs = 1000 m / s, and the maximum particle vibration velocity of the earthquake background noise is 0.15 μm / s. The helicopter maintains a flight altitude of 80 meters and a speed of 70 m / s. The sound pressure level of the acoustic signal generated by the helicopter during flight is 150 dB (at standard atmospheric pressure).

[0029] A method for advanced detection of low-altitude helicopters based on acoustic-vibration coupling is characterized by the following steps:

[0030] a. Analyze the background noise of the deployment site, select a relatively quiet site, and bury the seismic detector at a depth of 0.3m underground. The average particle vibration velocity of the seismic background noise is 0.15μm / s.

[0031] b. Deploy a seismic detector array, a total of 30 arrays, with an array spacing of 500 meters. Each array contains 50 array elements (seismic detectors) with a sensitivity of 2 cm / s / V. The correlation coefficient between the seismic background noise received by each array element is less than 0.05.

[0032] c. For the superimposed and denoised seismic signal, after acquiring the helicopter seismic signal, for the j-th array group, calculate the relative time delay between the signal with the highest signal-to-noise ratio among the array elements and the signals of other array elements. Then, sum all the array element signals in the j-th array group after calibrating the time delay to obtain the superimposed and denoised seismic signal S. j (n), where n is the sampling point number, j = 1, 2, ..., 30, n = 1, 2, ..., N, N is the sampling length, and the sampling frequency is 1000Hz;

[0033] d. Analyze the frequency of the leading wave excited by the helicopter. The velocities of the P-wave and S-wave underground at the array deployment site are 1400 m / s and 1000 m / s, respectively. The helicopter's flight speed is 70 m / s. Calculate |S j The sampling point number n0 corresponding to the maximum amplitude in the signal (n)| is then calculated to obtain S. j (n) In the time-frequency diagram, the frequency F0 corresponding to n0 is 28Hz. The frequency values ​​of the leading P-wave and leading S-wave are calculated using the leading wave Doppler frequency shift formula.

[0034] f wp =1.053F0, f ws =1.075F0 (1)

[0035] To obtain f wp and f ws They are 29.5Hz and 30.1Hz respectively;

[0036] e. Determine the frequency range of the leading wave, let A j It is S j The earliest arriving signal in (n), A j Find A, which arrives earliest in the time-frequency domain and whose frequency value does not change over time. j frequency F C f wp and f ws It also satisfies the following relationship

[0037] F0 < f wp <f ws <F C (2)

[0038] Formula (2) is f for step d. wp and f ws The results once again confirm that the frequency of the leading wave is more reliable. j F in the spectrum C If the width of half a spectral peak is 3 Hz, then the frequency range of the leading wave is [26.5, 33.1];

[0039] f. S j (n) After bandpass filtering in the [26.5, 33.1] frequency band, B is obtained. j (n), select the A1 portion of B1(n) and combine it with B j (n) Perform cross-correlation detection to obtain C j (n);

[0040] g. Time-of-arrival pickup of leading waves

[0041] |C j (n)| 2 >mean(|C j (n)| 2 )+X1·std(|C j (n)| 2 (3)

[0042] Where X1 is the weight parameter at time, "·" indicates multiplication, mean() is the function to calculate the average of the one-dimensional array within the parentheses, std() is the function to calculate the standard deviation of the one-dimensional array within the parentheses, and the first value of n that satisfies formula (3) is denoted as n. j n j / 1000 is the arrival time of the leading wave (i.e., the detection time) corresponding to the j-th group, in seconds. Then, the arrival time of the leading wave for all arrays is calculated.

[0043] h. Determine the reliability of the detection timing. Let E(j) be the detection result of all array groups, and diff(E(j)) be the derivative of E(j).

[0044] |diff(E(j))| 2 >mean(|diff(E(j))| 2 )+X2·std(|diff(E(j))| 2 (4)

[0045] Where X2 is the reliability weight parameter, the minimum value of j that satisfies formula (4) is denoted as j0, then the detection results of the first j0 groups in E(j) are all reliable.

[0046] Depend on Figure 1 It can be observed that the method of this invention can detect leading waves exceeding 10 kilometers from noise. Figure 2 As can be seen in this embodiment, the method of the present invention can detect helicopters flying at low altitudes up to 11 kilometers away, and the detection time is about 20 seconds earlier than that of acoustic detection technology, which shows that the method of the present invention has good effectiveness.

Claims

1. A method for advanced detection of low-altitude helicopters based on acoustic-vibration coupling, characterized in that, Includes the following steps: a. Analyze the background noise of the deployment site, select a relatively quiet site, bury the seismic detector underground at a depth of not less than 0.3m, and collect a seismic background noise for at least 5 minutes. The average particle vibration velocity of the seismic background noise should not exceed 0.4μm / s. Otherwise, the detector needs to be buried deeper or the deployment site needs to be changed. b. Deploy arrays with seismic detectors as array elements, a total of J arrays, with an array spacing of not less than 500 meters. Each array has not less than 10 array elements and a sensitivity of not less than 2 cm / s / V. The array element spacing should be greater than the correlation radius of the random noise at the deployment site, so that the correlation coefficient between the seismic background noise received by each array element does not exceed 0.

2. c. For the superimposed and denoised seismic signal, after acquiring the helicopter seismic signal, for the j-th array group, calculate the relative time delay between the signal with the highest signal-to-noise ratio among the array elements and the signals of other array elements. Then, sum all the array element signals in the j-th array group after calibrating the time delay to obtain the superimposed and denoised seismic signal S. j (n), j = 1, 2, ..., J, n is the sampling point number, n = 1, 2, ..., N, N is the sampling length, and the sampling frequency is Fs, in Hz; d. Analyze the frequency of the leading waves generated by the helicopter, and obtain the underground P-wave and S-wave velocities V at the array deployment site by consulting regional geological data. p and V s The helicopter's flight speed V is obtained through radar sensing technology. f Find |S j The sampling point number n0 corresponding to the maximum amplitude in the signal (n)| is then calculated to obtain S. j (n) The frequency F0 corresponding to n0 in the time-frequency diagram is used to calculate the frequency values ​​of the leading P-wave and leading S-wave using the leading wave Doppler frequency shift formula. f wp =V p F0 / (V p -V f ),f ws =V s F0 / (V s -V f ) (1) e. Determine the frequency range of the leading wave, let A. j It is S j The earliest arriving signal in (n), A j Find A, which arrives earliest in the time-frequency domain and whose frequency value does not change over time. j frequency F C f wp and f ws It also satisfies the following relationship F0<f wp <f ws <F C (2) Formula (2) is f for step d. wp and f ws The results further confirm that the frequency of the lead wave is more reliable, and the frequency range of the lead wave is [f]. wp -W,f ws +W], where W is A j F in the spectrum C Half the width of a spectral peak; f. S j (n) in [f wp -W,f ws After bandpass filtering of the +W frequency band, B is obtained. j (n), select the A1 portion of B1(n) and combine it with B j (n) Perform cross-correlation detection to obtain C j (n); g. Timing of lead wave detection |C j (n)| 2 >mean(|C j (n)| 2 )+X1·std(|C j (n)| 2 ) (3) Where X1 is the weight parameter at time, "." indicates multiplication, mean() is the function to calculate the average of the one-dimensional array within the parentheses, std() is the function to calculate the standard deviation of the one-dimensional array within the parentheses, and the first value of n that satisfies formula (3) is denoted as n. j n j / Fs is the lead wave detection time corresponding to the j-th group, in seconds. Then, the lead wave detection time of all arrays is calculated. h. Determine the reliability of the detection timing. Let E(j) be the detection result of all array groups, and diff(E(j)) be the derivative of E(j). |diff(E(j))| 2 >mean(|diff(E(j))| 2 )+X2·std(|diff(E(j))| 2 ) (4) Where X2 is the reliability weight parameter, the minimum value of j that satisfies formula (4) is denoted as j0, then the detection results of the first j0 groups in E(j) are all reliable.

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