Method of using acoustic sensors to determine the closest distance to the target and intercepting it with depth bombs

Abstract

The present invention discloses a method for an acoustic sensor to determine the closest distance to a target and to intercept it using a depth bomb, wherein the method for an acoustic sensor to determine the closest distance to a target comprises: step S1, establishing a signal processing model of the acoustic sensor based on the Doppler motion principle, and obtaining the acoustic sensor t based on the signal processing model k The relationship between the weighted output at time t0 and the weighted output at time t1; Step S2, based on the acoustic sensor t k The relationship between the weighted output at time t and the weighted output at time t0 is used to analyze and process the target noise collected by the acoustic sensor; step S3, the nearest point is determined by using the slope ratio method; making full use of the characteristics of the target noise, comprehensively utilizing data analysis methods, and judging the point closest to the target by processing and analyzing the noise collected by the acoustic sensor, which is helpful for data processing efficiency, reduces the amount of algorithm calculation, and has strong real-time performance, and has important application value.

Description

Technical Field

[0001] The invention relates to the technical field of maneuvering target interception, and in particular to a method for judging the closest distance to a target by a vector hydrophone based on the Doppler motion principle and intercepting the maneuvering target by using a depth bomb. Background Art

[0002] A mobile target is a type of weapon that can automatically propel itself and sail at a predetermined course and depth, and can automatically guide itself to a target and destroy it. Compared with weapons such as mines, artillery, and missiles, mobile targets are highly offensive, well concealed, and have great destructive power, and are widely used in weapon combat.

[0003] The self-noise of a maneuvering target usually refers to the noise generated by the maneuvering target during its navigation process that interferes with the operation of its own detection system. It is related to the speed, depth, operating frequency and sea conditions of the maneuvering target. The sources of the self-noise of a maneuvering target are mainly mechanical noise, propeller noise and flow noise. Among them, mechanical noise occupies a dominant position under low speed and high sea condition level. At medium speed, flow noise is the dominant noise. When the speed exceeds 20km, although the flow noise increases with the increase of speed, the propeller noise begins to dominate, and the propeller cavitation noise will be the main noise source in the kilohertz frequency band.

[0004] At present, using suspended depth charges (abbreviated as depth charges) to intercept maneuvering targets is one of the combat methods for surface ships to defend against maneuvering targets. This combat method can effectively make up for the defects of inaccurate sonar warning information and directly detonate and kill maneuvering targets. Suspended depth charges are used to intercept maneuvering targets. First, they must have a certain area of ​​dispersion after launch. Secondly, they must be able to accurately measure the distance from the maneuvering target to each depth charge after launch, so that when the maneuvering target enters the effective range of the depth charge, the suspended depth charge can be detonated in real time to damage the maneuvering target. Making a certain dispersion area after the depth charge is launched belongs to the overall structure and trajectory design content, and the current technology is relatively mature. How to use a simple method to achieve passive ranging is a new technology that is particularly required for the development of suspended depth charges, and it is also one of its technical difficulties. Summary of the invention

[0005] In response to the above problems, the inventors provided a method for using an acoustic sensor based on the Doppler motion principle to determine the closest distance to a target and to intercept a maneuvering target using a depth charge. By effectively determining the instantaneous moment corresponding to the closest distance between the offensive and defensive targets, the inventors ensured that the suspended depth charge had the best effect on the incoming maneuvering target.

[0006] Specifically, according to a first aspect, the present invention provides a method for an acoustic sensor to determine the closest distance to a target, comprising:

[0007] Step S1: Establish a signal processing model of the acoustic sensor based on the Doppler motion principle; and obtain the acoustic sensor t based on the signal processing model. k The relationship between the weighted output at time t and time t0;

[0008] Step S2: Based on the acoustic sensor t k The relationship between the weighted output at time t and time t0 is used to analyze and process the target noise collected by the acoustic sensor;

[0009] Step S3: Determine the nearest point using the slope comparison method.

[0010] Furthermore, the step S1 comprises:

[0011] Assume that at time t, there are M irrelevant Doppler signals incident on the acoustic sensor, and the azimuth is recorded as The complex envelope of the signal is denoted by s0(t),s1(t),…,s M-1 (t), the Doppler frequencies are f0, f1, …, f M-1 , then the output x(t) of the vector hydrophone is expressed as:

[0012]

[0013] Among them, s m (t) represents the mth noise signal, a m represents the steering vector of the mth noise signal, f m represents the frequency of the mth noise signal, j represents the imaginary unit, π represents the circumference of a circle; n(t) represents additive white Gaussian noise;

[0014] Assume that s0(t) is a line spectrum signal with higher power in the radiation noise. is a low-power line spectrum or interference; weight the output of the vector hydrophone:

[0015]

[0016] Among them, ω represents the weight vector, ω H represents conjugate transpose; a0 represents the steering vector corresponding to the line spectrum with the largest intensity, and f0 represents the frequency of the line spectrum with the largest intensity;

[0017] The acoustic sensor k The relationship between the weighted output at time t and time t0 is:

[0018]

[0019] Wherein, ΔT represents the Doppler delay.

[0020] Furthermore, in step S2, the step of analyzing and processing the target noise includes:

[0021] The target noise collected by the acoustic sensor is subjected to envelope demodulation, filtering, resampling and smoothing in sequence.

[0022] Furthermore, the step S3 comprises:

[0023] Fit the smoothed data and obtain the segmented slope when:

[0024] When , the current point is the closest point; if it does not meet the requirements, a target alarm is issued;

[0025] Among them, B represents the current slope, A represents the slope of the first two points, and C represents the slope of the last two points.

[0026] Furthermore, the envelope demodulation and filtering extracts signal data in a frequency band of 10kHz to 20kHz through a bandpass filter.

[0027] Furthermore, the resampling is to sample the original filtered data once every 10 points to obtain low-density data that is easy to analyze, that is, the resampling rate is 1 / 10.

[0028] Furthermore, the smoothing step is 30, that is, smoothing is performed once every 30 points, and the results are stored to form a new data group to be analyzed.

[0029] According to a second aspect, the present invention further provides a method for intercepting a mobile target using a depth charge, comprising the method for determining the closest distance to the target by the acoustic sensor as described above, and further comprising:

[0030] At the corresponding moment of the closest point determined by the slope comparison method, the suspended depth bomb is detonated to destroy the mobile target.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] (1) The present invention does not have expression redundancy. It is based on the Doppler motion principle, fully utilizes the characteristics of target noise, and comprehensively utilizes data analysis methods. After data preprocessing, slope comparison is performed without envelope extraction. This not only improves data processing efficiency and reduces algorithm calculation volume, but also has strong real-time performance.

[0033] (2) Compared with the existing passive ranging technology of suspended depth charges, the slope comparison method of the present invention is dedicated to determining the closest distance between a maneuvering target and a suspended depth charge, that is, determining the moment when the maneuvering target moves from approaching the depth charge to moving away from it, rather than the effective range of the suspended depth charge, and thus has important application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1A flowchart of the method for the acoustic sensor in Example 1 to determine the closest distance to the target and intercept it using a depth bomb;

[0035] Figure 2 It is a curve diagram of simulated data envelope demodulation and bandpass filtering in Example 2;

[0036] Figure 3 The simulated data resampling and smoothing curve diagram in Example 2;

[0037] Figure 4 It is the slope ratio curve diagram of the simulation data in Example 2;

[0038] Figure 5 It is the curve diagram of the experimental data envelope demodulation and bandpass filtering in Example 3;

[0039] Figure 6 The experimental data resampling and smoothing curve diagram in Example 3;

[0040] Figure 7 This is the slope year-on-year curve of the test data in Example 3. DETAILED DESCRIPTION

[0041] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0042] The Doppler effect occurs between objects in relative motion: the wavelength of radiation from an object changes due to the relative motion between the wave source and the observer. In front of the moving wave source, the wave is compressed, the wavelength becomes shorter, and the frequency becomes higher; behind the moving wave source, the opposite effect occurs, the wavelength becomes longer, and the frequency becomes lower. The higher the speed of the wave source, the greater the effect. Therefore, in the process of a target attacking another target, as the target and the other target get closer to each other, the noise level of the target changes. When the target is closest to the other target, the target noise power detected by the acoustic sensor is the largest, and the Doppler effect is most obvious.

[0043] Example 1

[0044] In this embodiment, the acoustic sensor is a vector hydrophone.

[0045] Based on the above Doppler effect, Figure 1 As shown, the present invention provides a method for an acoustic sensor to determine the closest distance to a target and intercept it using a depth bomb, comprising:

[0046] Step S1: Establish a signal processing model of the vector hydrophone based on the Doppler motion principle; and obtain the vector hydrophone t based on the signal processing model. k The relationship between time t and the weighted output at time t0.

[0047] Specifically, it is assumed that there is additive Gaussian white noise in the output signal of the vector hydrophone, and the noise is a zero-mean wide-stationary random process and is uncorrelated. Suppose at time t, there are M incoherent Doppler signals incident on the vector hydrophone, and the azimuth is recorded as The complex envelope of the signal is denoted by s0(t),s1(t),…,s M-1 (t), the Doppler frequencies are f0, f1, …, f M-1 , then the output x(t) of the vector hydrophone is expressed as:

[0048]

[0049] Among them, s m (t) represents the mth noise signal, a m represents the steering vector of the mth noise signal, f m represents the frequency of the mth noise signal, j represents the imaginary unit, π represents the circumference of a circle, and n(t) represents additive white Gaussian noise.

[0050] Assuming that the line spectrum, interference and noise used in the analysis process are unrelated, when the line spectrum is completely extracted, according to the Doppler effect, assuming that s0(t) is the line spectrum signal with higher power in the radiated noise, For low-power line spectrum or interference, in order to completely suppress the interference and effectively extract the line spectrum, the output of the vector hydrophone is weighted:

[0051]

[0052] Among them, ω represents the weight vector, ω H represents conjugate transpose; a0 represents the steering vector corresponding to the line spectrum with the largest intensity, and f0 represents the frequency of the line spectrum with the largest intensity;

[0053] Vector hydrophone k The relationship between the weighted output at time t and time t0 is:

[0054]

[0055] Wherein, ΔT represents the Doppler delay.

[0056] From the above formula, we can see that when More towards The larger the Doppler delay ΔT, the k The greater the change in the weighted output of the vector hydrophone at time t0.

[0057] Step S2: Based on the above principle, the maneuvering target noise collected by the vector hydrophone is subjected to envelope demodulation, filtering, resampling and smoothing processing in sequence.

[0058] Among them, envelope demodulation is to perform Hilbert transform on the sampled data to obtain the sound intensity. The sampled signal is a wide-band signal. In order to facilitate distinction and signal processing, different signals are in different frequency bands. Generally, noise is in the low-frequency band, so the envelope demodulated signal is passed through a bandpass filter to extract the signal data in this band.

[0059] Resampling is to sample the original filtered data every 10 points to obtain low-density data that is easy to analyze, that is, the resampling rate is 1 / 10.

[0060] The smoothing step is 30, that is, smoothing is performed every 30 points, and the results are stored to form a new data group to be analyzed.

[0061] Step S3: After obtaining the filtered and smoothed data, the slope ratio method is used to determine the closest point, and the suspended depth bomb is detonated at the time corresponding to the closest point.

[0062] Fit the filtered smoothed data to obtain the segmented slope. As the maneuvering target approaches, the slope gradually increases. When the maneuvering target is closest to the suspended depth bomb, the curve reaches an extreme value, and then the slope gradually decreases, and the slopes between two adjacent points are basically equal. Assume that B represents the current slope, A represents the slope of the first two points, and C represents the slope of the last two points. When it satisfies When the current point corresponding to the current slope is the closest point, the suspended depth bomb will be detonated at the current moment; if it is not satisfied, a target alarm will be issued.

[0063] It should be noted that the method provided by the present invention for using an acoustic sensor to determine the closest distance to a target can also be applied to the activation of a smart camera in the wild that is in a long-term standby state. Different types of wild animals have different acoustic characteristics. Therefore, when the acoustic sensor determines that an animal has reached the location of the smart camera, the camera is activated to start the detection work. After the wild animal moves away, the smart camera enters the standby state again. In addition, the method provided by the present invention for using an acoustic sensor to determine the closest distance to a target can also be applied to airports to prevent bird damage. Generally, airports use the physiological habits of birds to set up bird-repelling means, mainly including gas cannons, recording bird-repelling, visual deterrence, etc. Once an emergency occurs in which the above-mentioned bird-repelling means fail, that is, birds approach the danger zone of the airport, an alarm is sounded and the birds closest to the danger zone are intercepted, such as automatically setting nets and driving them away with shotguns.

[0064] Example 2

[0065] Use ideal simulation data to simulate and explain. The known simulation data meets the law of sinusoidal signal change. The simulation results are as follows Figure 2-4 shown.

[0066] Figure 2 Figures (a) and (b) show the signal envelope demodulation and bandpass filtering results respectively. Figure 3 Figures (a) and (b) in the figure show the resampled and smoothed curves respectively. Figure 1 and Figure 2 It can be seen that the changing trends of the four box diagrams are basically the same, except that the number of data points gradually decreases with different preprocessing steps. Figure 4 The slope year-on-year results are shown. Since the simulation data used is relatively ideal, and based on the changing characteristics of the sinusoidal signal, it can be seen that the slope change law is the same as the basic data change law.

[0067] Example 3

[0068] In this test, the data sampling rate f s =200kHz, if the data with length T_length = 0.1s is selected for analysis, the number of original data sampling points is f s ×T_length, that is, 20,000 points.

[0069] The data is demodulated by signal envelope and bandpass filtered, and the results are as follows: Figure 5 As shown in (a) and (b) in .

[0070] Assume that the resampling rate and smoothing step size are the same as those in the above simulation, that is, the resampling rate is 1 / 10 and the smoothing step size is 30. After resampling, the number of sampling data points changes from the original 20,000 points to 20,000 / 10=2000 points; after smoothing, the number of sampling data points changes from 2000 points to 2000 / 30=660 points. The results are as follows: Figure 6 As shown in (a) and (b) in .

[0071] Perform slope comparison on the preprocessed data, that is, perform linear fitting to find the slope, such as Figure 7 The slope change curve of the test data obtained by the slope comparison method is shown in the figure. The position of is determined as the best detonation point for the maneuvering target. Figure 7 It can be seen that when the horizontal axis is 235, the slope ratio has the maximum value. Therefore, the instantaneous time of the original data point corresponding to this point is the closest point of the maneuvering target to the suspended depth bomb, which can be used as the detonation point.

[0072] The above specific examples are used to illustrate the present invention, which is only used to help understand the present invention and is not intended to limit the present invention. For those skilled in the art, according to the concept of the present invention, some simple deductions, modifications or substitutions can be made.

Claims

1. A method for determining the closest distance to a target by an acoustic sensor, characterized in that: include: Step S1: Establishing a signal processing model of an acoustic sensor based on the Doppler motion principle; Based on the signal processing model, the acoustic sensor t k The relationship between the weighted output at time t and time t0; Step S2: Based on the acoustic sensor t k The relationship between the weighted output at time t and time t0 is used to analyze and process the target noise collected by the acoustic sensor; Step S3: Determine the closest point using the slope comparison method; Step S1 includes: Assume that at time t, there are M incoherent Doppler signals incident on the acoustic sensor, and the azimuth is recorded as The complex envelope of the signal is denoted by s0(t),s1(t),…,s M-1 (t), the Doppler frequencies are f0, f1, …, f M-1 , then the output x(t) of the vector hydrophone is expressed as: Among them, s m (t) represents the mth noise signal, a m represents the steering vector of the mth noise signal, f m represents the frequency of the mth noise signal, j represents the imaginary unit, π represents the circumference of a circle; n(t) represents additive white Gaussian noise; Assume that s0(t) is a line spectrum signal with higher power in the radiation noise. is a low-power line spectrum or interference; weight the output of the vector hydrophone: Among them, ω represents the weight vector, ω H represents conjugate transpose; a0 represents the steering vector corresponding to the line spectrum with the largest intensity, and f0 represents the frequency of the line spectrum with the largest intensity; The acoustic sensor k The relationship between the weighted output at time t and time t0 is: Where ΔT represents the Doppler delay; In step S2, the step of analyzing and processing the target noise includes: The target noise collected by the acoustic sensor is subjected to envelope demodulation, filtering, resampling and smoothing processing in sequence; The step S3 comprises: Fit the smoothed data and obtain the segmented slope when: When , the current point is the closest point; if it does not meet the requirements, a target alarm is issued; Among them, B represents the current slope, A represents the slope of the first two points, and C represents the slope of the last two points.

2. The method according to claim 1, characterized in that The envelope demodulation and filtering extracts signal data in a frequency band of 10kHz to 20kHz through a bandpass filter.

3. The method according to claim 1, characterized in that The resampling is to sample the original filtered data once every 10 points to obtain low-density data that is easy to analyze, that is, the resampling rate is 1 / 10.

4. The method according to claim 1, characterized in that The smoothing step is 30, that is, smoothing is performed every 30 points, and the results are stored to form a new data group to be analyzed.

5. A method for intercepting a mobile target using a depth charge, characterized in that: The method for determining the closest distance to a target by an acoustic sensor as claimed in any one of claims 1 to 4 further comprises: At the corresponding moment of the closest point determined by the slope comparison method, the suspended depth bomb is detonated to destroy the mobile target.

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