A method and system for detecting a supersonic target near the water surface based on an acoustic buoy array

Abstract

The application belongs to the technical field of acoustic signal detection, and discloses a supersonic target detection method and system near water surface based on an acoustic buoy array. First, a cross-air-sea medium attenuation prediction model is constructed to realize the matching of supersonic target radiation noise near water surface to underwater propagation signals. Second, the maximum energy and minimum distance method is used to automatically select acoustic buoy alarm units, joint positioning technology is used to expand measurement information, background noise and interference outside the joint positioning area are eliminated, and the information to be processed is obtained. Third, the TBD is used to select the information to be processed, Hough transform processing is performed on the information to be processed, and the initial point track set of the target, noise and interference satisfying the approximate straight line motion of the track is obtained. Finally, the speed, acceleration, heading angle and heading angle change rate and other motion elements are set to constrain the initial point track set, the noise and interference point tracks are eliminated, the real track of the target is obtained, and the supersonic target detection near water surface is completed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of acoustic signal detection, in particular to a near-surface supersonic target detection method and system based on an acoustic buoy array. BACKGROUND

[0002] The near-surface supersonic target has a high speed and a low flight height, which greatly improves the success rate of its low-altitude attack on water surface ships. In view of the serious threat of such targets to the safety of water surface ships, domestic and foreign researchers and technical personnel mainly rely on shipborne radars to detect them to achieve early warning. However, the shipborne radar detection is limited by the curvature of the earth and the target echo signal is easily disturbed by sea clutter, which restricts the detection area and detection probability, resulting in poor timeliness of the alarm and high subsequent blocking cost-effectiveness. In order to achieve supersonic flight, the near-surface supersonic target needs a high-power power propulsion system. During the launch phase, the pre-entry near-surface navigation phase, the near-surface navigation phase, and after hitting the water surface ship, it will produce a lot of radiated noise. The existing literature only studies the detection of the radiated noise of the target by acoustic sensors in the air. The speed of sound in the air is about 1 Mach (340 meters per second), but the speed of the near-surface supersonic target is greater than this value, and the acoustic sensor cannot effectively achieve early warning. When sound is transmitted from air to water, the propagation speed will be greatly improved, and the propagation speed in water is about 1500 meters per second (close to 4.4 Mach). Therefore, by taking advantage of the speed of sound in water, using underwater acoustic sensors to detect the radiated noise of the target entering the water from the air makes it possible to use acoustic sensors for early warning of near-surface supersonic targets.

[0003] As one of the underwater applications of acoustic sensors, acoustic buoys are widely used in marine forecasting, environmental monitoring, underwater detection and other fields. Acoustic buoys can be carried on different platforms on land, sea and air, and can be deployed flexibly. They can be passively detected and have good concealment. They are far away from the deployment platform and are less disturbed by platform noise. However, the physical properties of the target radiated noise will change significantly when it propagates from air to water, especially the energy will decay rapidly. The background noise and interference caused by natural environment such as thunderstorm, wind and wave surge, marine animals such as dolphin group and shrimp, underwater and water surface vehicles in working state, etc. can easily drown the weak target radiated noise. In addition, it is difficult to achieve reliable detection of the target signal obtained by a single acoustic buoy.

[0004] TBD theory and Hough transform are one of the hot research directions of weak target detection, which are widely used in the detection of weak targets such as near space super high speed vehicles and complex underwater acoustic environment vehicles, and have technical advantages in the detection of targets moving in an approximate straight line. In view of the problems existing in the passive detection of near water surface supersonic targets, by analyzing the radiation noise of the near water surface supersonic target and the characteristics of the air-sea medium, a cross air-sea medium attenuation prediction model is constructed, the acoustic buoy alarm array is reasonably arranged for detection preprocessing, the TBD theory and Hough transform are used to process the measurement information to be detected, and the effective detection of the near water surface supersonic target is realized. SUMMARY

[0005] The application provides a near water surface supersonic target detection method based on an acoustic buoy array, which breaks the limitation that the near water surface supersonic target mainly relies on electromagnetic wave detection, solves the problems of weak target signal, strong background noise and interference after the cross air-sea medium propagation attenuation, and weak detection capability of a single buoy sonar, and thus expands the adaptability of the TBD theory and Hough transform technology and the feasibility of the passive detection of the near water surface supersonic target by the acoustic buoy array.

[0006] To achieve the above object, the application provides the following scheme.

[0007] A near water surface supersonic target detection method based on an acoustic buoy array comprises the following steps.

[0008] Step 1: Construct a cross air-sea medium attenuation prediction model to realize the matching of the underwater propagation signal of the radiation noise of the near water surface supersonic target; the motion speed of the near water surface supersonic target is not more than 4 Mach;

[0009] Step 2: Automatically select the acoustic buoy alarm unit by using the maximum energy and minimum distance method, expand the measurement information by using the joint positioning technology of the alarm buoy unit, eliminate the background noise and interference outside the joint positioning area, and obtain the information to be processed; the acoustic buoy is a passive buoy sonar with a direction finding function;

[0010] Step 3: Select the information to be processed by using the TBD theory, process the information to be processed by using the Hough transform, eliminate most of the background noise and interference, and obtain an initial point track set of the target, noise and interference meeting the approximate straight line motion of the track;

[0011] Step 4: Set the motion elements such as speed, acceleration, heading angle and heading angle change rate to constrain and process the initial point track set, eliminate the noise and interference point tracks, obtain the real track of the target, and complete the detection of the near water surface supersonic target.

[0012] Optionally, step 1 specifically comprises the following steps.

[0013] Suppose that the supersonic target near the water surface moves approximately in a straight line. The supersonic target radiation noise exists sound energy attenuation in the process of across air-sea medium propagation. Considering the influence of sound velocity, attenuation rate, viscosity and heat loss, Prandtl number, boundary layer thickness, underwater sound propagation refractive index, Doppler shift and other factors, the sound energy attenuation prediction model across air-sea medium is constructed, the energy change prediction of supersonic target radiation noise from air into water at k time is realized, and the energy change prediction value at k time is

[0014] e as(k) =F(v (k) ,p r(k) ,t h(k) ,r e(k) ,Δf (k) ,r d(k) ,l vh(k) )

[0015] In the formula: v is sound velocity, r d is attenuation rate, l vh is viscosity and heat loss, p r is Prandtl number, t h is boundary layer thickness, r e is underwater sound propagation refractive index, and Δf is Doppler shift.

[0016] Optionally, step two specifically includes:

[0017] Suppose that any sonar in the acoustic buoy alarm array has the same performance and data synchronization. In the detection range of the alarm array, the measured energy obtained by detecting each acoustic buoy is acquired, and the acoustic buoy alarm unit is determined according to the maximum value of the signal energy and the minimum value of the adjacent spacing. Suppose that the acoustic buoy alarm array is composed of N passive direction-finding sonar buoys with adjacent spacing d. In the coordinate system Oxy, the position coordinates of the buoys are (x si ,y si )(i=1, 2, …, N), and the k time measured data set of the i th acoustic buoy is Z i ={z ki |k=1, 2, …, K}. The k time received data set of the i th acoustic buoy is

[0018] z ki ={(α k(i)j ,e k(i)j )|j=1, 2, …,n j}

[0019] In the formula: n j is the number of measurements, α k(i)j is the azimuth angle of the j th measurement, and e k(i)j is the energy of the j th measurement.

[0020] The energy set measured by the i acoustic buoy at time k is

[0021] {e k(i)j (i = 1, 2, …, N, j = 1, 2, …, n j )

[0022] The jthmeasurement energy of the i acoustic buoy at time k is

[0023] e k(i)j (i = 1, 2, …, N, j = 1, 2, …, n as(kij) ) no(kij) (i = 1, 2, …, N, j = 1, 2, …, n jim(kij) ) j )

[0024] e as(kij) , e no(kij) , e jim(kij) .

[0025] The maximum value method is used to search for the maximum energy value, and the corresponding acoustic buoy is i * .

[0026]

[0027] The decision threshold is N s / 2, N s is the number of acoustic buoy alarm arrays, and N is the buoy accumulation matrix.

[0028] According to the maximum energy value formula, further search for the acoustic buoy alarm array to obtain the second maximum energy value of two buoys i1 * and i2 * .

[0029] The minimum distance method is used to search for the distance between the buoy i * and the buoys i1 * and i2 * , and the corresponding acoustic buoy is i ** .

[0030] r(i * ,i ** ) = min{r(i * ,i1 * ), r(i * ,i2 * )

[0031] r(i * ,i1 * ) is the distance between the buoy i * and the buoy i1 *The distance between the acoustic buoy alarm unit (i * and the acoustic buoy alarm unit (i * ) is r(i * ). The distance between the acoustic buoy alarm unit (i * and the acoustic buoy alarm unit (i * ).

[0032] The acoustic buoy alarm unit (i ** ) is used to obtain the measurement information z * (i ** ).

[0033] In the plane coordinate system Oxy, the measurement information z ki (i * ) is obtained by using the alarm buoy unit (i ** ), the measurement (x k(i*)j , y k(i*)j , e k(i*)j ) containing the position information is obtained by using the joint positioning technology, and the background noise and interference outside the joint positioning area are eliminated to realize the extension of the measurement information.

[0034] Optionally, step three specifically includes:

[0035] The TBD theory is used to select the information segment to be processed, the measurement information in K (5≤K≤7) continuous time instants is randomly selected in time sequence to obtain the measurement point set Z k to be detected. In the coordinate system Oxy, the measurement point set at the k time instant is

[0036] Z k = {(x i*k , y i*k , e i*k )} (k=1,…,K).

[0037] The data space A={Z1,…,Z K}, the parameter space B, the cumulative matrix D and the energy accumulation matrix E are constructed, and the B, D and E are initialized.

[0038] The random Hough transform detection is performed on A and B, and most of the background noise and interference are eliminated to obtain the initial point track set of the target, noise and interference satisfying the approximate straight line motion of the track. The point number and energy double threshold accumulation formula is

[0039]

[0040] In the formula, (θ t , ρ m ) represents the center point coordinates of each parameter unit in B, and “+=” is the accumulation operation.

[0041] If the initial point track does not exist, steps

[0035] -

[0038] are repeated.

[0042] Optionally, step four specifically comprises:

[0043] If the track is detected in step three, the track constraint processing is performed, the data points of any adjacent k, k+1, k+2 moments in the initial track are selected, the motion elements such as velocity, acceleration, heading angle and heading angle change rate are calculated, and the initial track is processed by constraint.

[0044]

[0045] In the formula: v xmax is the maximum value of the x-direction velocity, v ymax is the maximum value of the y-direction velocity, v k is the velocity value in the energy change prediction value.

[0046] According to the prior information such as the sound energy attenuation prediction value, the initial tracks that meet the constraint conditions are merged, and the initial tracks that do not meet the constraint conditions are eliminated, so as to eliminate noise and interference tracks and obtain a target track with high fitting degree, that is, the detection of the near-surface supersonic target is completed.

[0047] The application also provides a near-surface supersonic target detection system based on an acoustic buoy array, which comprises:

[0048] The cross-air-sea medium sound energy attenuation prediction module utilizes the radiation noise of the near-surface supersonic target and the characteristics of the air-sea medium to construct a cross-air-sea medium attenuation prediction model, so as to realize the matching of the underwater propagation signal of the radiation noise of the near-surface supersonic target; the motion speed of the near-surface supersonic target is not more than 4 Mach.

[0049] The acoustic buoy alarm unit processing module determines the array type, the buoy spacing and the number of the acoustic buoy alarm array according to the distance between the near-surface supersonic target and the surface ship and the meteorological and hydrological conditions; after the acoustic buoy receives the underwater acoustic signal, the signal is transmitted back to the water acoustic signal processing system through a radio device; the maximum energy and minimum spacing method is used to automatically select the acoustic buoy alarm unit; the joint positioning technology of the alarm buoy unit is used to expand the measurement information and eliminate the background noise and interference outside the joint positioning area, so as to obtain the information to be processed; the acoustic buoy is a passive buoy sonar with a direction finding function.

[0050] The TBD and Hough transform processing module uses the TBD theory to select the information to be processed, processes the information to be processed by Hough transform, eliminates most of the background noise and interference, and obtains an initial track set of targets, noise and interference that meet the approximate straight line motion of the track.

[0051] The trajectory constraint processing module calculates motion elements such as velocity, acceleration, heading angle and heading angle rate, and performs constraint processing on the initial trajectory, eliminates noise and interference trajectory, and obtains a real trajectory of the target, i.e., completes detection of the near-surface supersonic target.

[0052] Optionally, the air-sea medium sound energy attenuation prediction module specifically comprises:

[0053] The air-sea medium sound energy attenuation prediction unit considers the influence of factors such as sound velocity, attenuation rate, viscosity and heat loss, Prandtl number, boundary layer thickness, underwater sound propagation refractive index, Doppler frequency shift, and constructs an air-sea medium sound energy attenuation prediction model.

[0054] Suppose that the near-surface supersonic target moves approximately in a straight line. The supersonic target radiation noise exists sound energy attenuation in the air-sea medium propagation process. The sound energy attenuation prediction value of the near-surface supersonic target radiation noise from air into water at k time is

[0055] e as(k) =F(v (k) ,p r(k) ,t h(k) ,r e(k) ,Δf (k) ,r d(k) ,l vh(k) )

[0056] Wherein, v is the sound velocity, r d is the attenuation rate, l vh is the viscosity and heat loss, p r is the Prandtl number, t h is the boundary layer thickness, r e is the underwater sound propagation refractive index, and Δf is the Doppler frequency shift.

[0057] Optionally, the acoustic buoy alarm unit processing module specifically comprises:

[0058] The acoustic buoy alarm array deployment unit determines the array type, buoy spacing and number of the acoustic buoy alarm array according to the distance between the near-surface supersonic target and the surface ship and the meteorological and hydrological conditions; the acoustic buoy is a passive buoy sonar with direction finding function.

[0059] Suppose that the acoustic buoy alarm array is composed of N passive direction finding sonar buoys with adjacent spacing d. In the coordinate system Oxy, the buoy position coordinates are (x si ,y si )(i=1,2,…,N), and the kth measurement data set of the ith acoustic buoy is Z i ={z ki |k=1,2,…,K}. The kth received data set of the ith acoustic buoy is

[0060] z ki = {(a k(i)j , e k(i)j )|j = 1, 2, …, n j}

[0061] where n j is the number of measurements, a k(i)j is the azimuth angle of the jthmeasurement, and e k(i)j is the energy of the jthmeasurement.

[0062] Optionally, the set of energy measurements of the ithacoustic buoy at time k is

[0063] {e k(i)j |i = 1, 2, …, N, j = 1, 2, …, n j}

[0064] Optionally, the jthmeasurement of the ithacoustic buoy at time k is

[0065] e k(i)j ∈ {e as(kij) , e no(kij) , e jim(kij)}(i = 1, 2, …, N, j = 1, 2, …, n j )

[0066] where e as(kij) is the target energy value, e no(kij) is the energy value of the background noise, and e jim(kij) is the energy value of the interference.

[0067] The acoustic-electric conversion and signal return unit, after the acoustic buoy receives the underwater acoustic signal, returns it to the water acoustic signal processing system through the radio equipment.

[0068] The acoustic buoy alarm selection unit automatically selects the acoustic buoy alarm unit using the maximum energy and minimum spacing method.

[0069] Optionally, the maximum value method is used to search for the maximum energy value, and the corresponding acoustic buoy is i * .

[0070]

[0071] where the decision threshold is N s / 2, N s is the number of buoys in the acoustic buoy alarm array, and N is the buoy accumulation matrix.

[0072] According to the maximum energy value formula, further search for the acoustic buoy alarm array to obtain the second maximum energy value of two buoys i1 * and i2 *.

[0073] Optionally, the minimum distance method is used to search the distance between the buoy i * and the buoy i1 * and the distance between the buoy i * and the buoy i2 ** .

[0074] r(i * ,i ** )=min{r(i * ,i1 * ),r(i * ,i2 * )}

[0075] Wherein, r(i * ,i1 * ) is the distance between the buoy i * and the buoy i1 * , and r(i * ,i2 * ) is the distance between the buoy i * and the buoy i2 * .

[0076] The acoustic buoy alarm unit is (i * ,i ** ).

[0077] The joint positioning underwater acoustic signal unit uses the alarm buoy unit to jointly position the underwater acoustic signal, eliminates the background noise and interference outside the joint positioning area, and obtains the information to be processed.

[0078] In the plane coordinate system Oxy, the measurement information z ki (i=i * ,i ** ) is obtained by using the alarm buoy unit (i * ,i ** ), the measurement (x k(i*)j , y k(i*)j , e k(i*)j ) containing the position information is obtained by using the joint positioning technology, and the background noise and interference outside the joint positioning area are eliminated, so that the measurement information is extended.

[0079] Optionally, the TBD and Hough transform processing module specifically includes:

[0080] The TBD and Hough transform processing module uses the TBD theory to select the information to be processed, performs Hough transform processing on the information to be processed, eliminates most of the background noise and interference, and obtains the initial point track set of the target, noise and interference satisfying the approximate straight line motion of the track.

[0081] The TBD selects a to-be-processed information segment unit, utilizes the TBD theory to obtain a to-be-detected measurement point set Z according to time sequence by randomly selecting measurement information in K (5≤K≤7) continuous time points k In the coordinate system Oxy, the measurement point set at the k time point is

[0082] Z k = {(x i*k ,y i*k, e i*k )} (k=1,..., K).

[0083] The Hough transform processing unit performs Hough transform processing on the to-be-processed information segment, and eliminates most of the background noise and interference to obtain an initial track set of the target, noise and interference satisfying the approximate straight line motion of the track.

[0084] The data space A={Z1,..., Z K}, the parameter space B, the cumulative matrix D and the energy accumulation matrix E are constructed, and the B, D and E are initialized.

[0085] The random Hough transform detection is performed on A and B, and most of the background noise and interference are eliminated to obtain an initial track set of the target, noise and interference satisfying the approximate straight line motion of the track.

[0086] Optionally, the point number and energy double threshold accumulation formula is

[0087]

[0088] Wherein, (θ t ,ρ m ) represents the center point coordinates of each parameter unit in B, and "+" is an accumulation operation.

[0089] If the initial track does not exist, steps

[0081] -

[0085] are repeated.

[0090] Optionally, the track constraint processing module specifically comprises:

[0091] The track constraint processing module, if the detected track exists in the TBD and Hough transform processing module, performs track constraint processing, selects data points at any adjacent k, k+1 and k+2 time points in the initial track, and calculates the velocity, acceleration, heading angle and heading angle change rate and other motion elements to perform constraint processing on the initial track.

[0092] The velocity constraint processing unit, in the coordinate system Oxy, the velocity constraint condition is

[0093]

[0094] Wherein, v xmaxis a maximum value of the velocity in the x direction, v ymax is a maximum value of the velocity in the y direction, v k is a velocity value in the energy change prediction value.

[0095] is an acceleration constraint processing unit, and the acceleration constraint condition is

[0096]

[0097] is a heading angle constraint processing unit, and the heading angle constraint condition is

[0098]

[0099] is a heading angle change rate constraint processing unit, and the heading angle change rate constraint condition is

[0100]

[0101] According to the prior information such as the sound energy attenuation prediction value, the initial point tracks meeting the constraint conditions are merged, and the initial point tracks not meeting the constraint conditions are eliminated, so that the noise and interference point tracks are eliminated, and the target point track with high fitting degree is obtained, that is, the detection of the near-surface supersonic target is completed.

[0102] According to the specific embodiments provided by the present application, the present application discloses the following technical effects: the present application provides a near-surface supersonic target detection method and system based on an acoustic buoy array, which comprises the following steps: a cross-air-sea medium attenuation prediction model is constructed to realize the matching of the underwater propagation signal of the near-surface supersonic target radiation noise; the movement speed of the near-surface supersonic target is not more than 4 Mach; the maximum energy and minimum distance method is used to automatically select an acoustic buoy alarm unit; the alarm buoy unit is used to jointly locate the underwater acoustic signal to obtain a to-be-detected measurement point set; the acoustic buoy is a passive buoy sonar with a direction-finding function; the to-be-detected measurement point set is subjected to TBD and Hough transform processing to obtain an initial point track set; if the initial point track set exists, the initial point track set is subjected to constraint processing to obtain a target real track, so that the detection of the near-surface supersonic target is realized. BRIEF DESCRIPTION OF DRAWINGS

[0103] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0104] Figure 1 The present application provides a near-surface supersonic target detection method based on an acoustic buoy array, and the flowchart is as follows:

[0105] Figure 2 The implementation flowchart of the near-surface supersonic target detection method based on the acoustic buoy array provided for the embodiment 1 of the present application is shown in the figure;

[0106] Figure 3 The construction principle diagram of the cross-air-sea medium attenuation prediction model provided for the embodiment 1 of the present application is shown in the figure;

[0107] Figure 4 The automatic selection of the acoustic buoy alarm unit provided for the embodiment 1 of the present application is shown in the figure;

[0108] Figure 5 The joint positioning of the acoustic buoy alarm unit provided for the embodiment 1 of the present application is shown in the figure;

[0109] Figure 6 The TBD and Hough transform algorithm flowchart provided for the embodiment 1 of the present application is shown in the figure;

[0110] Figure 7 The plot constraint processing method diagram provided for the embodiment 1 of the present application is shown in the figure;

[0111] Figure 8 The system block diagram of the near-surface supersonic target detection system based on the acoustic buoy array provided for the embodiment 2 of the present application is shown in the figure. DETAILED DESCRIPTION

[0112] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0113] The main shortcomings of the acoustic buoy detecting the near-surface supersonic target in the prior art include:

[0114] The conventional acoustic sensor is only used for detecting the air target below 1 Mach.

[0115] Because the propagation speed of the acoustic wave in the air is lower than the motion speed of the near-surface supersonic target, the TBD theory and the Hough transform technology cannot be directly used for detecting the near-surface supersonic target.

[0116] In view of the above shortcomings of the prior art, the purpose of the present application is to provide a near-surface supersonic target detection method and system based on an acoustic buoy array, so as to expand the application of the acoustic buoy and the TBD theory and the Hough transform technology in the field of near-surface supersonic target detection.

[0117] Embodiment 1

[0118] Example 1 provides a method for detecting a near-surface supersonic target based on an acoustic buoy array, as shown in Figure 1 and Figure 2 , the method comprising:

[0119] Step 1: Construct a cross-air-sea medium attenuation prediction model to realize the matching of the underwater propagation signal of the near-surface supersonic target radiation noise; the movement speed of the near-surface supersonic target is not more than 4 Mach;

[0120] Step 2: Automatically select the acoustic buoy alarm unit by using the maximum energy and minimum distance method, use the alarm buoy unit joint positioning technology to expand the measurement information, and eliminate the background noise and interference outside the joint positioning area to obtain the information to be processed; the acoustic buoy is a passive buoy sonar with direction finding function.

[0121] Step 3: Use the TBD theory to select the information segment to be processed, perform Hough transform processing on the information segment to be processed, and eliminate most of the background noise and interference to obtain an initial track set of the target, noise and interference that meet the approximate straight line motion of the track;

[0122] Step 4: Calculate the movement elements such as speed, acceleration, heading angle and heading angle change rate to constrain the initial track set and eliminate noise and interference tracks to obtain the real track of the target, that is, the detection of the near-surface supersonic target is completed.

[0123] The process of constructing the cross-air-sea medium attenuation prediction model in this embodiment will be introduced as follows:

[0124] As shown in Figure 3 , it is assumed that the near-surface supersonic target moves approximately in a straight line. The supersonic target radiation noise exists in the sound energy attenuation in the cross-air-sea medium propagation process. A general model of the near-surface supersonic target radiation noise is constructed, considering the influence of factors such as sound speed, attenuation rate, viscosity and thermal loss, Prandtl number, boundary layer thickness, underwater sound propagation refractive index, Doppler shift, etc. The sound attenuation coefficient is calculated, the cross-air-sea medium sound energy attenuation prediction model is constructed, and the prediction of the energy change of the near-surface supersonic target radiation noise when it enters the water from the air is realized. The energy change prediction value at time k is

[0125] e as(k) =F(v (k) ,p r(k) ,t h(k) ,r e(k) ,Δf (k) ,r d(k) ,l vh(k) ) (1)

[0126] In the formula: v is the sound speed, r d is the attenuation rate, l vhviscosity and thermal losses, p r Prandtl number, t h boundary layer thickness, r e sound speed in water, Δf Doppler shift.

[0127] In this embodiment, see Figure 4 , the second step of automatically selecting the acoustic buoy alarm unit is introduced:

[0128] Assume that any sonar in the acoustic buoy alarm array has the same performance and data synchronization. Within the detection range of the alarm array, the acoustic buoy alarm unit is determined according to the maximum value of the signal energy and the minimum value of the adjacent interval by detecting the measurement energy obtained by each acoustic buoy. Assume that the acoustic buoy alarm array is composed of N passive direction-finding sonar buoys with an adjacent interval of d. In the coordinate system Oxy, the coordinates of the buoy position are (x si ,y si )(i = 1, 2, …, N), and the measurement data set of the i-th acoustic buoy at time k is Z i ={z ki |k = 1, 2, …, K}. The received data set of the i-th acoustic buoy at time k is

[0129] z ki ={(α k(i)j ,e k(i)j )|j = 1, 2, …, n j} (2)

[0130] where n j is the number of measurements, α k(i)j is the azimuth angle of the j-th measurement, and e k(i)j is the energy of the j-th measurement.

[0131] The energy set measured by the i-th acoustic buoy at time k is

[0132] {e k(i)j |i = 1, 2, …, N, j = 1, 2, …, n j} (3)

[0133] According to the azimuth angle of the passive acoustic buoy received measurement, the energy of the j-th measurement of the i-th acoustic buoy at time k is

[0134] e k(i)j ∈{e as(kij) ,e no(kij) ,e jim(kij)}(i = 1, 2, …, N, j = 1, 2, …, n j ) (4)

[0135] where e as(kij) is the target energy value, eno(kij) e represents the energy value of the background noise. jim(kij) This represents the energy value of the interference.

[0136] See Figure 5 The maximum energy value is searched using the maximum value method, and the corresponding acoustic buoy is i. * .

[0137]

[0138] In the formula: the decision threshold is N s / 2,N s Let N be the number of buoys in the acoustic buoy warning array, and N be the buoy accumulation matrix.

[0139] Further searching the acoustic buoy warning array using the maximum energy value formula yielded two buoys i1 with the second-highest energy values. * and i2 * .

[0140] Searching for buoy i using the minimum spacing method * With buoy i1 * and buoy i2 * The spacing, whose corresponding acoustic buoy is i ** .

[0141] r(i * i ** )=min{r(i * i1 * ),r(i * i2 * (6)

[0142] In the formula: r(i * i1 * ) for buoy i * With buoy i1 * The spacing, r(i) * i2 * ) for buoy i * With buoy i2 * The spacing.

[0143] The acoustic buoy alarm unit is (i * i ** ).

[0144] The process of constructing the trans-air-sea medium attenuation prediction model in this embodiment is described below:

[0145] In this embodiment, see Figure 5 The method of joint positioning of acoustic buoy alarm units in step two will be introduced:

[0146] In the plane coordinate system Oxy, the measurement information z * (i ** ) is obtained by the warning buoy unit (i ki (i * ,i ** ), the measurement (x k(i*)j ,y k(i*)j ,e k(i*)j ) containing position information is obtained by using the joint positioning technology, the background noise and interference outside the joint positioning area are eliminated, and the measurement information extension is realized.

[0147] In the embodiment, as shown in Figure 6 , the TBD theory and the Hough transform algorithm in step three specifically include:

[0148] Step 1: The information segment to be processed is selected by using the TBD theory. According to the time sequence, the measurement information in K (5≤K≤7) continuous time instants is selected to obtain the measurement point set Z k to be detected. In the coordinate system Oxy, the measurement point set at the k time instant is

[0149] Z k ={(x i*k ,y i*k ,e i*k )}(k=1,…,K) (7)

[0150] Step 2: The data space A={Z1,…,Z K}, the parameter space B, the cumulative matrix D and the energy accumulation matrix E are constructed, and the B, D and E are initialized.

[0151] Step 3: The random Hough transform detection is performed on A and B, and most of the background noise and interference are eliminated to obtain the initial point trail set of the target, noise and interference satisfying the approximate straight line motion of the track. The point number and energy double threshold accumulation formula is

[0152]

[0153] In the formula, (θ t ,ρ m ) represents the center point coordinates of each parameter unit in B, and “+=” is the accumulation operation.

[0154] If the initial point trail does not exist, steps 1-3 are repeated.

[0155] In the embodiment, as shown in Figure 7 , the method of the point trail constraint processing in step four specifically includes:

[0156] If the detection point exists in step three, the point constraint processing is carried out, the data points of any adjacent k, k+1, k+2 moments in the initial point are selected, and the velocity, acceleration, heading angle and heading angle change rate and other motion elements are calculated to constrain the initial point.

[0157] Step 1: velocity constraint processing, in the coordinate system Oxy, the velocity constraint condition is

[0158]

[0159] In the formula: v xmax is the maximum value of the x-direction velocity, v ymax is the maximum value of the y-direction velocity, v k is the velocity value in the energy change prediction value.

[0160] Step 2: acceleration constraint processing, the acceleration constraint condition is

[0161]

[0162] Step 3: heading angle constraint processing, the heading angle constraint condition is

[0163]

[0164] Step 4: heading angle change rate constraint processing, the heading angle change rate constraint condition is

[0165]

[0166] According to the prior information such as the energy change prediction value, the initial points meeting the constraint condition are combined, and the initial points not meeting the constraint condition are eliminated, so that the noise and interference points are eliminated, and the target point with high fitting degree is obtained. That is, the detection of the near-surface supersonic target is completed.

[0167] Compared with the prior art, the near-surface supersonic target detection method based on the acoustic buoy array has the beneficial effects that:

[0168] (1) The present application uses the constructed cross-space-sea medium sound energy attenuation prediction to realize the matching of the near-surface supersonic target radiation noise underwater propagation signal.

[0169] (2) The present application uses the constructed acoustic buoy alarm unit to realize joint positioning, expand the measurement information, and eliminate the background noise and interference outside the joint positioning area to obtain the information to be processed.

[0170] (3) The present application uses the existing TBD and Hough transform technology in the weak target detection field to realize the detection of the near-surface supersonic target moving in an approximate straight line.

[0171] Embodiment 2

[0172] The embodiment provides a near-surface supersonic target detection system based on an acoustic buoy array, referring to Figure 8 , the system comprises:

[0173] The cross-air-sea medium sound energy attenuation prediction module T1 utilizes near-surface supersonic target radiation noise and air-sea medium characteristics to construct a cross-air-sea medium attenuation prediction model, and realizes matching of the near-surface supersonic target radiation noise with underwater propagation signals; the motion speed of the near-surface supersonic target is not more than 4 Mach;

[0174] The acoustic buoy alarm unit processing module T2 determines the array type, the buoy spacing and the number of the acoustic buoy alarm array according to the distance between the near-surface supersonic target and the surface ship and the meteorological and hydrological conditions; after the acoustic buoy receives underwater acoustic signals, the underwater acoustic signals are transmitted back to the water acoustic signal processing system through a radio device; the maximum energy and minimum spacing method is used to automatically select the acoustic buoy alarm unit; the underwater acoustic signal is jointly located by using the alarm buoy unit; background noise and interference outside the joint location area are eliminated; and the processed information is obtained; the acoustic buoy is a passive buoy sonar with a direction finding function.

[0175] The TBD and Hough transform processing module T3 uses the TBD to select the processed information segment, performs Hough transform processing on the processed information segment, eliminates most of the background noise and interference, and obtains an initial point track set of the target, noise and interference satisfying the approximate straight line motion of the track;

[0176] The point track constraint processing module T4 performs constraint processing on the initial point track by calculating motion elements such as speed, acceleration, heading angle and heading angle change rate, eliminates noise and interference point tracks, and obtains a real target track, that is, the near-surface supersonic target detection is completed.

[0177] In the embodiment, the cross-air-sea medium sound energy attenuation prediction module T1 specifically comprises:

[0178] The cross-air-sea medium sound energy attenuation prediction unit constructs a cross-air-sea medium sound energy attenuation prediction model by considering the influence of factors such as sound velocity, attenuation rate, viscosity and heat loss, Prandtl number, boundary layer thickness, underwater sound propagation refractive index and Doppler frequency shift;

[0179] It is assumed that the near-surface supersonic target approximately performs straight line motion. The sound energy of the supersonic target radiation noise attenuates during the propagation in the cross-air-sea medium. The sound energy attenuation prediction value of the near-surface supersonic target radiation noise after entering the water from the air at time k is

[0180] e as(k) =F(v (k) ,p r(k) ,t h(k)r e(k) ,Δf (k) ,r d(k) ,l vh(k) )

[0181] where v is the sound speed, r d is the attenuation rate, l vh is the viscosity and thermal loss, p r is the Prandtl number, t h is the boundary layer thickness, r e is the underwater sound propagation refractive index, and Δf is the Doppler shift.

[0182] In the embodiment, the acoustic buoy alarm unit to be processed module T2 specifically comprises:

[0183] An acoustic buoy alarm array deployment unit determines the array type, the buoy spacing and the number of the acoustic buoy alarm array according to the distance between the supersonic target near the water surface and the surface ship and the meteorological and hydrological conditions; the acoustic buoy is a passive buoy sonar with a direction finding function.

[0184] Suppose that the acoustic buoy alarm array is composed of N passive direction finding sonar buoys with an adjacent spacing of d. In the coordinate system Oxy, the buoy position coordinates are (x si ,y si )(i=1, 2, …, N), and the measurement data set of the i-th acoustic buoy at the k-th moment is Z i ={z ki |k=1, 2, …, K}. The received data set of the i-th acoustic buoy at the k-th moment is

[0185] z ki ={(α k(i)j ,e k(i)j )|j=1, 2, …, n j}

[0186] where n j is the number of measurements, α k(i)j is the azimuth angle of the j-th measurement, and e k(i)j is the energy of the j-th measurement.

[0187] Optionally, the energy set measured by the i-th acoustic buoy at the k-th moment is

[0188] {e k(i)j |i=1, 2, …, N, j=1, 2, …, n j}

[0189] Optionally, the energy of the j-th measurement of the i-th acoustic buoy at the k-th moment is

[0190] e k(i)j ∈{e as(kij) ,eno(kij) ,e jim(kij)}(i=1,2,…,N,j=1,2,…,n j )

[0191] where e as(kij) is the target energy value, e no(kij) is the energy value of background noise, and e jim(kij) is the energy value of interference.

[0192] The sound-electricity conversion and signal feedback unit is used to feed back the underwater acoustic signal received by the acoustic buoy to the water acoustic signal processing system through the radio equipment.

[0193] The acoustic buoy alarm selection unit is used to automatically select the acoustic buoy alarm unit by using the maximum energy and minimum distance method.

[0194] Optionally, the maximum value method is used to search for the maximum energy value, and the corresponding acoustic buoy is i * .

[0195]

[0196] where the decision threshold is N s / 2, N s is the number of buoys in the acoustic buoy alarm array, and N is the buoy accumulation matrix.

[0197] According to the maximum energy value formula, the acoustic buoy alarm array is further searched to obtain the second maximum energy value of two buoys i1 * and i2 * .

[0198] Optionally, the minimum distance method is used to search for the distance between the buoy i * and the buoys i1 * and i2 * , and the corresponding acoustic buoy is i ** .

[0199] r(i * ,i ** )=min{r(i * ,i1 * ),r(i * ,i2 * )}

[0200] where r(i * ,i1 * ) is the distance between the buoy i * and the buoy i1 * , and r(i * ,i2 * ) is the distance between the buoy i * and the buoy i2 * .

[0201] The acoustic buoy alarm unit is used for (i * ,i ** ).

[0202] The joint positioning underwater acoustic signal unit is used for jointly positioning the underwater acoustic signal by the alarm buoy unit, eliminating the background noise and interference outside the joint positioning area, and obtaining the information to be processed.

[0203] In the plane coordinate system Oxy, the measurement information z * (i ** ) is obtained by the alarm buoy unit (i ki ,i * ,i ** ), the measurement (x k(i*)j ,y k(i*)j ,e k(i*)j ) containing the position information is obtained by using the joint positioning technology, and the background noise and interference outside the joint positioning area are eliminated to realize the extension of the measurement information.

[0204] In the embodiment, the TBD and Hough transform processing module T3 specifically comprises:

[0205] The TBD and Hough transform processing module is used for selecting the information segment to be processed by using the TBD theory, performing the Hough transform processing on the information segment to be processed, eliminating most of the background noise and interference, and obtaining the initial point track set of the target, noise and interference satisfying the approximate straight line motion of the track.

[0206] The TBD unit is used for selecting the information segment to be processed by using the TBD theory, obtaining the measurement point set Z k in the coordinate system Oxy, and the measurement point set at the k time is

[0207] Z k ={(x i*k ,y i*k ,e i*k )}(k=1,…,K).

[0208] The Hough transform processing unit is used for performing the Hough transform processing on the information segment to be processed, eliminating most of the background noise and interference, and obtaining the initial point track set of the target, noise and interference satisfying the approximate straight line motion of the track.

[0209] The data space A={Z1,…,Z K}, the parameter space B, the cumulative matrix D and the energy accumulation matrix E are constructed, and the B, D and E are initialized.

[0210] Random Hough transform is performed on A and B to detect and eliminate most of the background noise and interference, and an initial track set of targets, noise and interference satisfying the approximate straight line motion of the track is obtained.

[0211] Optionally, the point number and energy double threshold accumulation formula is

[0212]

[0213] wherein, (θ t ,ρ m ) represents the center point coordinates of each parameter unit in B, and "+" is an accumulation operation.

[0214] If the initial track does not exist, repeat steps

[00205] -

[00210] .

[0215] In the embodiment, the track constraint processing module T4 specifically comprises:

[0216] The track constraint processing module, if the detected track in the TBD and Hough transform processing module exists, performs track constraint processing, selects data points at any adjacent k, k+1, k+2 time points in the initial track, and calculates velocity, acceleration, heading angle and heading angle change rate and other motion elements to perform constraint processing on the initial track.

[0217] The velocity constraint processing unit, in the coordinate system Oxy, the velocity constraint condition is

[0218]

[0219] wherein, v xmax is the maximum value of the x-direction velocity, v ymax is the maximum value of the y-direction velocity, and v k is the velocity value in the energy change prediction value.

[0220] The acceleration constraint processing unit, the acceleration constraint condition is

[0221]

[0222] The heading angle constraint processing unit, the heading angle constraint condition is

[0223]

[0224] The heading angle change rate constraint processing unit, the heading angle change rate constraint condition is

[0225]

[0226] According to the prior information such as energy change prediction value, the initial point traces meeting the constraint condition are merged, the initial point traces not meeting the constraint condition are eliminated, the noise and interference point traces are eliminated, and the target point trace with high fitting degree is obtained. That is, the supersonic target near the water surface is detected.

[0227] For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant part can be referred to the method part.

[0228] The principles and implementation manners of the present application are described by using specific examples in the present application, and the above embodiment description is only used for helping to understand the method of the present application and the core idea thereof; meanwhile, for the general technical personnel in the field, the specific implementation manner and application range will be changed according to the idea of the present application. In conclusion, the content of the present application should not be understood as the limitation of the present application.

Claims

1. A method for detecting near-surface supersonic targets based on an acoustic buoy array, characterized in that, include: Step 1: Construct a trans-air-sea medium acoustic energy attenuation prediction model to match the underwater propagation signal of supersonic target radiation noise near the water surface; The speed of a supersonic target near the water surface does not exceed Mach 4; Step 2: The acoustic buoy alarm unit is automatically selected using the maximum energy and minimum spacing method. The measurement information is expanded by using the acoustic buoy alarm unit joint positioning technology, and background noise and interference outside the joint positioning area are eliminated to obtain the information to be processed. The acoustic buoy is a passive buoy sonar with direction finding function. Step 3: Select the information segment to be processed using TBD theory, perform Hough transform on the information segment to be processed, and eliminate most of the background noise and interference to obtain the initial set of target, noise and interference that satisfies the approximate straight-line motion of the track. Step 4: Set motion elements such as velocity, acceleration, heading angle, and rate of change of heading angle to constrain the initial point set, eliminate noise and interference points, and obtain the true target trajectory, thus completing the detection of supersonic targets near the water surface. Step one specifically includes: Assuming that the supersonic target near the water surface moves approximately in a straight line, the radiated noise of the supersonic target will experience sound energy attenuation during the propagation of the air-sea medium; Considering the influence of sound speed, attenuation rate, viscosity and heat loss, Prandtl number, boundary layer thickness, underwater sound propagation refractive index, and Doppler frequency shift, a trans-air-sea medium sound energy attenuation prediction model is constructed to predict the energy of supersonic target radiation noise entering the water from the air near the water surface. The predicted energy is then used to match the radiation noise of supersonic target on the water surface.

2. The method for detecting near-surface supersonic targets based on an acoustic buoy array according to claim 1, characterized in that, Step two specifically includes: Assume the acoustic buoy warning array consists of adjacent buoys spaced at intervals of... of Composed of 10 passive direction-finding sonar buoys The acoustic buoys receive a set of energy values ​​at any given time, and then search for the buoy with the highest energy value in the acoustic alarm buoy array according to the maximum energy value formula. and two buoys with the second-highest energy value and Calculate the buoys separately With buoys and buoys Spacing , Then, the corresponding acoustic buoy is searched according to the minimum spacing formula. In a plane coordinate system In the middle, using alarm buoy units and Acquiring measurement information , Measurements containing location information are obtained using joint positioning technology. It also eliminates background noise and interference outside the joint positioning area, thereby expanding the measurement information.

3. The method for detecting near-surface supersonic targets based on an acoustic buoy array according to claim 1, characterized in that, Step three specifically includes: Using TBD theory to select information segments to be processed, and arbitrarily selecting consecutive segments according to time sequence. The measurement information within a given time period is used to obtain the set of measurement points to be detected. , in ; Constructing a data space Parameter space Cumulative matrix and energy accumulation matrix and to , and Initialization processing; for and Random Hough variation detection is performed, and most background noise and interference are eliminated to obtain an initial set of target, noise and interference that satisfies the approximate straight-line motion of the trajectory.

4. The method for detecting near-surface supersonic targets based on an acoustic buoy array according to claim 1, characterized in that, Step four specifically includes: If the detected points exist in step three, point constraint processing is performed, selecting any adjacent points from the initial points. , , The data points at each time point are used to calculate the motion elements such as velocity, acceleration, heading angle, and rate of change of heading angle, and then constrain the initial point trace.

5. A near-surface supersonic target detection system based on an acoustic buoy array, characterized in that, include: The trans-air-sea medium acoustic energy attenuation prediction module utilizes the radiated noise of supersonic targets near the water surface and the characteristics of the air-sea medium to construct a trans-air-sea medium acoustic energy attenuation prediction model, thereby achieving the matching of the underwater propagation signal of the radiated noise of supersonic targets near the water surface. The speed of a supersonic target near the water surface does not exceed Mach 4; The acoustic buoy alarm unit processing module determines the array configuration, spacing, and number of acoustic buoys based on the distance between nearby supersonic targets and surface ships, as well as meteorological and hydrological conditions. After receiving underwater acoustic signals, the acoustic buoys transmit the signals back to the surface acoustic signal processing system via wireless equipment. The system automatically selects acoustic buoy alarm units using the maximum energy and minimum spacing method, and uses the acoustic buoy alarm units to jointly locate underwater acoustic signals, eliminating background noise and interference outside the joint location area to obtain the information to be processed. The acoustic buoys are passive buoy sonars with direction-finding capabilities. The TBD sampling and Hough transform processing module uses TBD theory to select the information segment to be processed, performs Hough transform processing on the information segment to be processed, and eliminates most of the background noise and interference, so as to obtain the initial point set of targets, noise and interference that satisfy the approximate straight-line motion of the track. The point constraint processing module sets motion elements such as velocity, acceleration, heading angle, and rate of change of heading angle to constrain the initial point, eliminate noise and interference points, and obtain the true target trajectory, thus completing the detection of supersonic targets near the water surface. The trans-air-sea medium acoustic energy attenuation prediction module specifically includes: A trans-air-sea medium acoustic energy attenuation prediction unit is constructed, assuming that the supersonic target near the water surface moves approximately in a straight line and that the radiated noise of the supersonic target experiences acoustic energy attenuation during its propagation in the trans-air-sea medium. Considering the influence of sound speed, attenuation rate, viscosity and heat loss, Prandtl number, boundary layer thickness, underwater sound propagation refractive index, and Doppler frequency shift, a trans-air-sea medium acoustic energy attenuation prediction model is built to predict the energy of the radiated noise of the supersonic target near the water surface as it enters the water. The predicted energy is then used to match the radiated noise of the supersonic target on the water surface.

6. A near-surface supersonic target detection system based on an acoustic buoy array according to claim 5, characterized in that, The acoustic buoy alarm unit's processing module specifically includes: The acoustic buoy warning array deployment unit determines the array type, buoy spacing, and number of acoustic buoys based on the distance between nearby supersonic targets and surface ships, as well as meteorological and hydrological conditions; the acoustic buoys are passive buoy sonars with direction-finding capabilities. The acoustic-to-electric conversion and signal transmission unit receives underwater acoustic signals and transmits them back to the underwater acoustic signal processing system via wireless equipment; the acoustic buoy alarm selection unit automatically selects the acoustic buoy alarm unit using the maximum energy and minimum spacing method. The joint positioning underwater acoustic signal unit utilizes the acoustic buoy alarm unit to jointly locate underwater acoustic signals and eliminates background noise and interference outside the joint positioning area to obtain the information to be processed.

7. A near-surface supersonic target detection system based on an acoustic buoy array according to claim 5, characterized in that, The TBD and Hough transform processing module specifically includes: TBD selects the information segment unit to be processed, and uses TBD theory to arbitrarily select measurement information within K consecutive time moments in chronological order to obtain the set of measurement points to be detected. ,in ; The Hough transform processing unit performs Hough transform processing on the information segment to be processed, and eliminates most of the background noise and interference, to obtain an initial set of target, noise and interference that satisfies the approximate straight-line motion of the trajectory.

8. A near-surface supersonic target detection system based on an acoustic buoy array according to claim 5, characterized in that, The point constraint processing module specifically includes: If the detected points exist in the TBD and Hough transform processing modules, point constraint processing is performed, selecting any adjacent points from the initial points. , , The data points at each moment are used to calculate the motion elements such as velocity, acceleration, heading angle, and rate of change of heading angle, and then constrain the initial point trace. Velocity constraint processing unit; Acceleration constraint processing unit; Heading angle constraint processing unit; Heading angle change rate constraint processing unit; Based on the prior information of the predicted energy change values, initial points that meet the constraints are merged, while initial points that do not meet the constraints are removed. This process eliminates noise and interference points, and obtains target points with high fitting degree, thus completing the detection of supersonic targets near the water surface.

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