WO2019095912A1 - 基于可调夹角均匀线阵的水下波达方向估计方法及装置 - Google Patents

基于可调夹角均匀线阵的水下波达方向估计方法及装置 Download PDF

Info

Publication number
WO2019095912A1
WO2019095912A1 PCT/CN2018/110446 CN2018110446W WO2019095912A1 WO 2019095912 A1 WO2019095912 A1 WO 2019095912A1 CN 2018110446 W CN2018110446 W CN 2018110446W WO 2019095912 A1 WO2019095912 A1 WO 2019095912A1
Authority
WO
WIPO (PCT)
Prior art keywords
array
angle
signal
matrix
incident
Prior art date
Application number
PCT/CN2018/110446
Other languages
English (en)
French (fr)
Inventor
宁更新
李晓鹏
谭纬城
张军
冯义志
季飞
Original Assignee
华南理工大学
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华南理工大学 filed Critical 华南理工大学
Publication of WO2019095912A1 publication Critical patent/WO2019095912A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/80—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves
    • G01S3/802—Systems for determining direction or deviation from predetermined direction
    • G01S3/803—Systems for determining direction or deviation from predetermined direction using amplitude comparison of signals derived from receiving transducers or transducer systems having differently-oriented directivity characteristics
    • G01S3/8034—Systems for determining direction or deviation from predetermined direction using amplitude comparison of signals derived from receiving transducers or transducer systems having differently-oriented directivity characteristics wherein the signals are derived simultaneously
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the invention relates to the technical field of underwater target positioning, in particular to an underwater wave direction estimation method and device based on a uniform angle uniform linear array.
  • DOA estimation spatial direction direction estimation
  • the subspace decomposition class algorithm is a high-resolution method developed in the 1970s. It can accurately estimate the parameters (frequency, azimuth, etc.) of the signal. Its performance ideal, resolution and estimation accuracy are better than traditional ones. The method is high and is therefore widely used in the field of DOA estimation.
  • the subspace decomposition class algorithm is characterized by appropriate mathematical transformation to decompose the received signal of the array into two subspaces that are orthogonal to each other, namely the signal subspace and the noise subspace, and then use the characteristics of the two types of subspaces to perform DOA. estimate. Therefore, the subspace decomposition class algorithm can be divided into two subspace algorithms: signal subspace and noise subspace.
  • the former is represented by the ESPRIT algorithm based on the subspace rotation invariant technique, and the latter is based on the multi-classification algorithm (MUSIC). Algorithm) is representative.
  • MUSIC belongs to the extreme value search method, and the ESPRIT algorithm belongs to the direct solution method. Therefore, the ESPRIT algorithm does not need to perform full-space spectral peak search, and its computational complexity is much smaller than the MUSIC algorithm.
  • the ESPRIT algorithm has the advantages of realistic and high resolution, so it is widely used in DOA estimation.
  • the existing method of estimating the direction of arrival using the ESPRIT algorithm has a low precision.
  • the propagation speed of the signal in the medium needs to be regarded as a known parameter.
  • the speed of sound is related to many environmental factors and is a constantly changing parameter. Therefore, using a fixed sound velocity parameter for underwater DOA estimation will produce a large error.
  • the existing line arrays used for the direction of arrival estimation are fixed angles. In the actual measurement process, multiple measurements can only be made for this fixed angle, which cannot effectively improve the estimation accuracy.
  • the main object of the present invention is to overcome the shortcomings of the above ESPRIT algorithm, and to provide an underwater wave direction estimation method based on a uniform angle array with adjustable angles, using a uniform linear array with two adjustable angles as a receiving array.
  • the propagation speed of the signal in the medium is eliminated, and multiple sets of measurements with different angles are obtained to obtain higher measurement accuracy than the existing DOA method.
  • Another object of the present invention is to provide an underwater direction of arrival estimating device based on a uniform angled array of adjustable angles, which can be set to measure a plurality of different line array angle values.
  • An underwater DOA estimation method based on a uniform angle uniform linear array includes the following steps:
  • Step 1 Establish an adjustable linear array model with an angle
  • Step 2 Establish a signal receiving model of two uniform linear arrays
  • the direction angles of the K narrow-band target sound sources corresponding to the horizontal line array are ⁇ nx1 , ⁇ nx2 , . . . , ⁇ nxK , respectively, and the direction angles corresponding to the oblique line array are respectively ⁇ ny1 . , ⁇ ny2 ,..., ⁇ nyK ; with the first array element as the reference point, the signal received by the first array element at time t is:
  • s i (t) represents the ith source signal and n 1 (t) represents the noise on the first array element
  • the received signal satisfies the narrowband condition, that is, when the signal delay is much smaller than the reciprocal of the bandwidth, the delay is equivalent to causing a phase shift of the baseband signal, and then the signal received by the mth array element at the same time is:
  • ⁇ i represents the wavelength of the acoustic wave reflected by the i-th target source
  • n m (t) represents the noise on the m-th array element
  • the received signal of each array element is arranged in the form of a column vector, then the signal received by the entire horizontal line array It can be represented by the following vector formula:
  • Step 3 Establish a uniform line array sub-array model, and derive the rotation operator ⁇ x and ⁇ y expressions;
  • the M array elements in the horizontal line array are divided into two sub-arrays Z hx and Z hy whose translation vectors are d; the sub-array Z hx is composed of the first to the M-1th array elements of the horizontal array, and then:
  • x h1 (t) x 1 (t)
  • x h2 (t) x 2 (t)
  • x h1 (t), x h2 (t), L, x h(M-1) (t) are the signals received by the first array element to the M- 1th array element on the sub-array Z hx , respectively ;
  • the sub-array Z hy is composed of the second to M-th array elements of the horizontal array, and there are:
  • y h1 (t), y h2 (t), L, y h(M-1) (t) are the signals received by the first array element to the M- 1th array element on the sub-array Z hy , respectively ;
  • n hxm (t) and n hym (t) are the additive noise of the mth array element on the sub-arrays Z hx and Z hy , respectively, and the above equation is written as a vector form:
  • the matrix ⁇ x is a diagonal matrix of K ⁇ K, which is a unitary matrix that links the outputs of the sub-arrays Z hx and Z hy , also called a rotation operator whose diagonal elements contain the wavefronts of K signals.
  • the phase delay information between any one of the array elements is expressed as:
  • the inclined uniform linear array can be divided into two sub-arrays Z vx and Z vy to obtain the received signals X v (t) and Y v (t), so that the rotation operator is:
  • Step 4 Establish a relationship between the rotation operators ⁇ x , ⁇ y and ⁇ nxi , ⁇ nyi ;
  • Step 5 Establish a relationship between two direction angles when the acoustic wave signal is incident from different regions;
  • Step 6 Pairing the diagonal elements on the matrix ⁇ x and the matrix ⁇ y ;
  • Step 7 Find the size of ⁇ nxi based on the pairing result.
  • step four specifically includes:
  • the covariance matrix of X h (t) can be expressed as:
  • R ss E ⁇ S(t)S H (t) ⁇ , which is the source part covariance matrix
  • ⁇ xi is a diagonal element on the matrix ⁇ x
  • ⁇ xi ⁇ x1 , ⁇ x2 , L, ⁇ xK ⁇ , i 1, 2, L, K;
  • the two covariance matrices R vxx and R vxy of the obliquely uniform array can be obtained by the same reason, and then the eigenvalues ⁇ y1 , ⁇ y2 , L are obtained by performing eigenvalue decomposition on the matrix bundle ⁇ C vxx , C vxy ⁇ , ⁇ yK , which also correspond one-to-one to the diagonal elements on the matrix ⁇ y , but the correspondence is also uncertain, and can be written by equation (3):
  • ⁇ yi is the diagonal element on the matrix ⁇ y
  • the specific step 5 includes:
  • the incident area of the acoustic signal is set to four: when ⁇ ⁇ (0, ⁇ n ), the acoustic signal is incident on the area 1; When ⁇ ( ⁇ n , ⁇ /2), the acoustic signal is incident on region 2; when ⁇ ( ⁇ /2, ⁇ /2+ ⁇ n ), the acoustic signal is incident on region 3; when ⁇ ( ⁇ /2) When + ⁇ n , ⁇ ), the acoustic signal is incident on the region 4;
  • ⁇ 1i is the angle between the incident direction of the sound wave and the normal of the horizontal line array
  • ⁇ 1j is the angle between the incident direction of the sound wave and the normal of the inclined line array
  • the reference array element receives the signal at the latest, and the array element in the sub-array Z hx receives the signal later than the corresponding array element in the sub-array Z hy , so that the delay can be obtained.
  • ⁇ nyi - ⁇ nxi + ⁇ n - ⁇ (6)
  • ⁇ nyi ⁇ nxi - ⁇ n (7)
  • ⁇ nyi ⁇ nxi - ⁇ n
  • ⁇ nyi ⁇ nxi - ⁇ n
  • step six specifically includes:
  • h i is the i-th element in the sequence ;
  • v i is the i-th element in the sequence V.
  • step seven Preferably, in step seven,
  • Underwater DOA estimation device based on adjustable angle uniform linear array, comprising data processing and control module, angle control module, transmitting module, receiving module, output module and power module; power module and data processing and control module , an angle control module, a transmitting module, a receiving module and an output module are connected, which can supply power to the modules;
  • the data processing and control module is the core part of the whole device. All other modules are directly connected to it; it can control the transmitting module to enable the transmitting module to transmit the specified signal; the angle control module can be controlled to turn the angle of the two uniform linear arrays To the set value; it is also possible to process the signal transmitted from the receiving module, calculate the direction of arrival angle, and then transmit the result to the transmitting module.
  • the data processing and control module is comprised of a pair of A/D, D/A converters and a processor.
  • the angle control module comprises a stepping motor and a driving circuit for controlling the angle between the two line arrays; the stepping motor is an open loop control motor for converting the electric pulse signal into an angular displacement or a line displacement, when driving
  • the circuit receives a pulse signal that drives the stepper motor to rotate a fixed angle in a set direction.
  • the data processing and control module can transmit a certain number of pulse signals to achieve a desired angle value.
  • the receiving module comprises two arrays of ultrasonic receiving probes, the angle between the two arrays is variable and the angle can be adjusted by the angle control module.
  • the horizontal array L1 and the stepping motor are fixed together, the array L2 is mounted on the stepping motor and the array L1 and the array L2 are in the same plane, and the array L2 can be rotated by the stepping motor to achieve the angle between the two lines.
  • the purpose of the adjustment is to achieve the angle between the two lines.
  • the fixing bracket is made of plastic material; the stator of the stepping motor is connected to the bracket, and the rotor of the stepping motor is connected to the array L2.
  • the transmitting module comprises an impedance matching circuit and an ultrasonic transmitting probe.
  • the output module comprises a USB interface and a display, which can provide human-computer interaction, and output the processed data in the data processing and control module to the external device through the USB interface or display on the display.
  • the present invention has the following advantages and beneficial effects:
  • the present invention is more practical and more accurate than the conventional ESPRIT algorithm for estimating the direction of arrival of underwater targets.
  • the traditional ESPRIT algorithm usually assumes that the speed of sound is a constant, and in the actual complex underwater environment, the speed of sound is often constantly changing. If it is calculated as a constant, it will lead to large errors.
  • the invention adopts a uniform linear array with two angles adjustable, and eliminates the variable speed of sound by the relationship between the angles of the two arrays and the direction of the direction of arrival, so that the final operation result is independent of the speed of sound, thereby improving the estimation accuracy.
  • the angle between the two line arrays is variable, multiple measurements can be made by taking different values, which can better eliminate the error.
  • the invention improves on the traditional ESPRIT algorithm, while retaining the advantages of high resolution of the ESPRIT algorithm, and the computational complexity and complexity of the improved algorithm are not excessively increased, which ensures the feasibility of the algorithm.
  • the device of the invention is improved on a conventional measuring device, and a uniform linear array with an angle adjustable agent is used, which is highly feasible and simple to install.
  • the continuous improvement of the computing power of modern processors makes the integration of chips such as processors used in the present invention high, and the computing power is strong, thereby ensuring the feasibility of the present invention.
  • 1 is a block diagram showing the hardware structure of an apparatus of an embodiment.
  • Figure 2 is a schematic diagram of the connection of the receiving module.
  • Figure 3 is a top view of the connection of the receiving module.
  • Figure 4 is a side view of the receiving module connection.
  • Figure 5 is a diagram of an adjustable angle uniform linear array used in the embodiment.
  • Figure 6 is a received signal model of a horizontally uniform line array.
  • Figure 7 is an adjustable angle uniform linear array model when the signal is incident from region 1.
  • Figure 8 is an adjustable angle uniform linear array model when the signal is incident from region 2.
  • Figure 9 is an adjustable angle uniform linear array model when the signal is incident from region 3.
  • Figure 10 is an adjustable angle uniform linear array model when the signal is incident from region 4.
  • Figure 11 is a flow chart of the method of the embodiment.
  • An underwater wave direction estimation method based on a uniform angle array with adjustable angles.
  • the factor of sound velocity can be eliminated in the direction of arrival estimation, thereby eliminating the uncertainty of underwater sound velocity.
  • the angle of the two uniform line arrays is variable, the angle can be changed for multiple measurements in the actual measurement to better eliminate the error.
  • Step 1 Establish an angled adjustable uniform linear array model, as shown in Figure 5. Placed in water two angles ⁇ n of the uniform linear array, a uniform linear array in the horizontal direction and an inclined linear arrays, are set to x and y axes. According to the angle between the line array ⁇ n and the angle between the incident direction of the sound wave and the positive axis of the x-axis, the incident area of the acoustic signal is set to four: when ⁇ ⁇ (0, ⁇ n ), the acoustic signal is incident on the area 1; When ⁇ ( ⁇ n , ⁇ /2), the acoustic signal is incident on region 2; when ⁇ ( ⁇ /2, ⁇ /2+ ⁇ n ), the acoustic signal is incident on region 3; when ⁇ ( ⁇ /2) When + ⁇ n , ⁇ ), the acoustic signal is incident on the region 4;
  • Step 2 Establish a signal reception model for two uniform linear arrays.
  • the angle of the line array is ⁇ n
  • the direction angles of the K narrow-band target sound sources corresponding to the horizontal line array are ⁇ nx1 , ⁇ nx2 , . . . , ⁇ nxK , respectively, and the direction angles corresponding to the oblique line array are respectively ⁇ ny1 . , ⁇ ny2 ,..., ⁇ nyK .
  • the model scenario of the horizontal uniform linear array is shown in Figure 6. Taking the first array element as the reference point, the signal received by the first array element at time t is:
  • s i (t) represents the ith source signal and n 1 (t) represents the noise on the first array element.
  • the received signal satisfies the narrowband condition, ie, when the signal delay is much less than the reciprocal of the bandwidth, the delay is equivalent to causing a phase shift in the baseband signal.
  • the signal received by the mth array element at the same time is:
  • ⁇ i represents the wavelength of the acoustic wave reflected from the i-th target source
  • n m (t) represents the noise on the m-th array element.
  • the received signals of the array elements are arranged in a column vector form, and the signals received by the entire horizontal line array can be represented by the following vector formula:
  • the signal reception model of the tilted uniform linear array can be obtained.
  • Step 3 Establish a uniform line array sub-array model and derive the rotation operator expression.
  • the M array elements in the horizontal line array are divided into two sub-arrays Z hx and Z hy whose translation vectors are d.
  • the sub-array Z hx is composed of the first to the M-1th array elements of the horizontal array, and there are:
  • x h1 (t) x 1 (t)
  • x h2 (t) x 2 (t)
  • x h1 (t), x h2 (t), L, x h(M-1) (t) are the signals received by the first array element to the M- 1th array element on the sub-array Z hx , respectively .
  • the sub-array Z hy is composed of the second to M-th array elements of the horizontal array, and there are:
  • y h1 (t), y h2 (t), L, y h(M-1) (t) are the signals received by the first array element to the M- 1th array element on the sub-array Z hy , respectively .
  • n hxm (t) and n hym (t) are the additive noise of the mth array element on the sub-arrays Z hx and Z hy , respectively.
  • the matrix ⁇ x is a diagonal matrix of K ⁇ K, which is a unitary matrix that links the outputs of the sub-arrays Z hx and Z hy , also called a rotation operator whose diagonal elements contain the wavefronts of K signals.
  • the phase delay information between any one of the array elements is expressed as:
  • the inclined uniform linear array can be divided into two sub-arrays Z vx and Z vy to obtain the received signals X v (t) and Y v (t), so that the rotation operator is:
  • Step 4 Establish the relationship between the rotation operators ⁇ x and ⁇ y and ⁇ nxi and ⁇ nyi .
  • the covariance matrix of X h (t) can be expressed as:
  • R ss E ⁇ S(t)S H (t) ⁇ is the source part covariance matrix.
  • ⁇ xi is the diagonal element on the matrix ⁇ x
  • the two covariance matrices R vxx and R vxy of the obliquely uniform array can be obtained by the same reason, and then the eigenvalues ⁇ y1 , ⁇ y2 , L are obtained by performing eigenvalue decomposition on the matrix bundle ⁇ C vxx , C vxy ⁇ , ⁇ yK , which also correspond one-to-one to the diagonal elements on the matrix ⁇ y , but the correspondence is also uncertain, and can be written by equation (3):
  • ⁇ yi is the diagonal element on the matrix ⁇ y
  • Step 5 Establish the relationship between the two direction angles when the acoustic signal is incident from different regions.
  • ⁇ 1i is the angle between the incident direction of the sound wave and the normal of the horizontal line array
  • ⁇ 1j is the angle between the incident direction of the sound wave and the normal of the inclined line array.
  • ⁇ 1i + ⁇ 1j ⁇ - ⁇ n . Since the array signal on the x-axis is the array element in the most negative direction of the x-axis, and the sub-array Z hx is also in the negative x-axis direction of the sub-array Z hy .
  • the reference array element receives the signal at the latest, and the array element in the sub-array Z hx receives the signal later than the corresponding array element in the sub-array Z hy , so that the delay can be obtained.
  • ⁇ nyi - ⁇ nxi + ⁇ n - ⁇ (6)
  • ⁇ nyi ⁇ nxi - ⁇ n (7)
  • ⁇ nyi ⁇ nxi - ⁇ n
  • ⁇ 4i is the angle between the incident direction of the sound wave and the normal of the horizontal line array
  • ⁇ 4j is the angle between the incident direction of the sound wave and the normal line of the inclined line array.
  • ⁇ nyi ⁇ nxi - ⁇ n
  • Step 6 Pair the diagonal elements ⁇ xi and ⁇ yi on the matrix ⁇ x and the matrix ⁇ y . According to formula (4) and formula (9), if the pairing is successful, the following formula holds:
  • h i is the i-th element in the sequence ;
  • v i is the i-th element in the sequence V.
  • Step 7 Find the size of ⁇ nxi based on the pairing result.
  • ⁇ n the corresponding direction of arrival angle
  • the improved algorithm proposed in this embodiment can accurately estimate ⁇ xi without knowing the magnitude of the sound velocity, that is, the value of the direction of arrival angle ⁇ xi can be estimated under the condition that the speed of sound is uncertain, and the algorithm can be overcome.
  • the shortcomings of the traditional ESPRIT algorithm At the same time, by changing the angle between the two line arrays and performing multiple estimations and finally averaging, the error can be effectively eliminated.
  • FIG. 1 A flowchart of the above method can be represented by FIG.
  • the underwater wave direction estimation device based on the adjustable angle uniform linear array provided in this embodiment is as shown in FIG. 1 , and includes a data processing and control module, an angle control module, a transmitting module, a receiving module, an output module, and a power module.
  • the data processing and control module consists of a pair of A/D, D/A converters and a processor, which is the core part of the entire device, and all other modules are directly connected to it. It can control the transmitting module to enable the transmitting module to transmit a specified signal; the angle control module can be controlled to turn the angle of the two uniform linear arrays to a set value; and the signal transmitted from the receiving module can also be processed, by Embodiment 1
  • the algorithm calculates the direction of arrival of the direction of arrival and then transmits the result to the transmitting module.
  • the angle control module is used to control the angle between the two line arrays, and is composed of a stepping motor and a driving circuit.
  • the stepping motor is an open-loop control motor that converts an electric pulse signal into an angular displacement or a linear displacement.
  • the driving circuit receives a pulse signal, it drives the stepping motor to rotate in a set direction at a fixed angle, called a step. angle. Therefore, the desired angle value can be achieved by causing the data processing and control module to transmit a certain number of pulse signals.
  • the receiving module is composed of two ultrasonic receiving probe arrays, the angle between the two arrays is variable and the angle can be adjusted by the angle control module.
  • the horizontal array L1 and the stepping motor are fixed together.
  • the array L2 is mounted on the stepping motor and ensures that the array L1 and the array L2 are on the same plane, and the array L2 can be rotated by the stepping motor to achieve the purpose of adjusting the angle of the two line arrays.
  • Figure 3 and Figure 4 show the top view and side view of the device connection.
  • the stepper motor stator is connected to the bracket, and the stepper motor rotor is connected to the array L2.
  • the two arrays can also receive signals transmitted from the target source and then A/D convert them to the processor.
  • the transmitting module consists of an impedance matching circuit and an ultrasonic transmitting probe, which is connected to the processor through a D/A converter and can transmit a specified signal according to an instruction issued by the processor.
  • the output module consists of a USB interface and a display and is connected to the data processing and control module and the power module. It can provide human-computer interaction, and output the processed data in the data processing and control module to the external device through the USB interface or display it on the display.
  • the power module is composed of a power source and is connected to the data processing and control module, the angle control module, the transmitting module, the receiving module, and the output module. It can power these modules.
  • the main working process of the device is as follows: in the actual measurement process, according to the signal parameters to be transmitted, the corresponding parameters are input through the data processing and control module, so that the processor generates a corresponding digital signal, and then transmits to the transmission through D/A conversion. Modules, ultrasonic transmitters can generate the signals we need and transmit.
  • the angle between the two line arrays can be set by the data processing and control module.
  • the processor sends a specific pulse signal to the drive circuit of the angle control module, and then the drive circuit can drive the stepper motor to rotate to the desired angle.
  • the receiving array in the receiving module receives the signal reflected from the target sound source, converts it into a digital signal through A/D, and sends it to the processor, and then the processor calculates the result according to the provided algorithm. Finally, the data processing and control module transmits the calculation result to the output module, and the output module transmits the result to the external device through the USB interface or through the display.
  • the power module supplies power to all other modules.
  • the device comprises a data processing and control module, an angle control module, a transmitting module, a receiving module, an output module and a power module.
  • the data processing and control module can be implemented by DSP chip (such as TI chip TMS320VC5509A DSP chip), which can realize A/D conversion and D/A conversion functions, and can realize the rotation operator of uniform linear array and The calculation of the final direction of arrival;
  • the angle control module includes a stepper motor and a drive circuit, using a stepping motor of the Fuxing HSTM42-1.8-D-26-4-0.4 model, the stepping angle of the stepping motor is 1.8 degrees.
  • the driving circuit adopts the ULN2003 chip; the transmitting module uses an ultrasonic transmitting probe; the receiving module uses two uniform linear arrays of adjustable angles, wherein each array includes a plurality of ultrasonic receiving probes, and the number is the same, and the two linear arrays are as shown in FIG.
  • FIG. 1 is a block diagram showing the hardware structure of the device of the present invention.
  • the angle of the line array is set, and the angle between the two line arrays is changed to 15° by the angle control module.
  • Four target sound sources were placed under water, and the angles with the horizontal array normals were 30°, 60°, -30°, and -60°, respectively.
  • the parameters of the transmitting module are set by the data processing and control module so that the frequency of the transmitted signal is 100 kHz and the pulse length is 5 ms.
  • Step 2 Sampling the target sound source signal received by the ultrasonic receiving probe; the horizontally uniform array receives the signals x x1 (t), x x2 (t), L, x x8 (t) and y x1 ( t), y x2 (t), L, y x8 (t), the signals received by the uniform array in the oblique direction are x y1 (t), x y2 (t), L, x y8 (t) and y y1 (t ), y y2 (t), L, y y8 (t).
  • the total sampling is received 200 times, and the received signal is transmitted to the data acquisition processing and control module for arithmetic processing.
  • Step 3 The processing steps of the signal in the data acquisition processing and control module are as follows:
  • Step 4 Store the calculated direction angle information and transmit it to the output module for output to an external device via the USB interface or display on the LCD display.
  • Step 5 Change the angle between the two line arrays, set to 30°, 45°, 60°, and 75° respectively. According to the results calculated by each calculation, the average value is 30° according to the algorithm. 60°, -30°, -60°, which is the same as the actual angle, indicating that the estimation result is correct, and the method and device are feasible.

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

一种基于可调夹角均匀线阵的水下波达方向估计方法及装置，采用两个夹角可以调节的均匀线阵(L1,L2)，通过两个阵列夹角与波达方向角之间的关系消去了声速这个变量，使得最后的运算结果与声速无关，从而提高了估计精度，同时由于两线阵夹角可变，通过取不同值进行多次测量，可以更好的消除误差。

Description

基于可调夹角均匀线阵的水下波达方向估计方法及装置 技术领域
本发明涉及水下目标定位的技术领域，特别涉及一种基于可调夹角均匀线阵的水下波达方向估计方法及装置。
背景技术
阵列信号处理技术在众多领域已得到广泛应用，而阵列信号处理的基本问题之一是空间信号波达方向估计(DOA估计)。DOA估计，即空间谱估计，所采用的处理方法是在噪声环境中摆放多个传感器组成阵列，以此来接收目标信号，然后对阵列的接收信号进行处理，最终估计出目标信号相对阵列的入射方向。子空间分解类算法是20世纪70年代发展起来的一种高分辨率方法，它能精确地估测出信号的参数(频率、方位等)，其性能理想、分辨能力和估测精度均比传统方法高，因此被广泛应用于DOA估计领域。子空间分解类算法的特点是通过适当的数学变换，将阵列的接收信号分解为相互正交的两个子空间，即信号子空间与噪声子空间，再利用两类子空间各自的特性来进行DOA估计。所以子空间分解类算法又可以分为信号子空间和噪声子空间两类子空间算法，前者以建立在子空间旋转不变技术的基础上的ESPRIT算法为代表，后者以多重分类算法(MUSIC算法)为代表。MUSIC属于极值搜索法，ESPRIT算法属于直接求解法，因此ESPRIT算法无需进行全空间谱峰搜索，其运算量远小于MUSIC算法。此外ESPRIT算法还具有现实可行、分辨率高的优点，所以在DOA估计中应用非常广泛。
但是，现有的利用ESPRIT算法进行波达方向估计的方法存在精度不高的问题，一方面，在用ESPRIT算法进行DOA估计过程中，需要把信号在介质中的传播速度当成一个已知参数，而在水下环境中，声速跟许多环境因素有关，是一个不断变化的参数，因此用一个固定的声速参数进行水下DOA估计会产生较大的误差。另一方面，现有的波达方向估计所用的线阵 都是固定夹角的，在实际测量过程中，只能针对这一固定的夹角进行多次测量，不能有效地提高估计精度。
发明内容
本发明的主要目的在于克服上述ESPRIT算法存在的缺点，提供一种基于可调夹角均匀线阵的水下波达方向估计方法，使用两个可调夹角的均匀线阵作为接收阵列，在算法过程中消去信号在介质中的传播速度，并且通过不同夹角的多组测量，来获得相比于现有的DOA方法更高的测量精度。
本发明的另一目的在于提供一种基于可调夹角均匀线阵的水下波达方向估计装置，该装置可以设置多个不同的线阵夹角值进行测量。
本发明的目的通过以下的技术方案实现：
一种基于可调夹角均匀线阵的水下波达方向估计方法，包括以下步骤：
步骤一：建立夹角可调均匀线阵模型；
在水中放置两个夹角为α n的均匀线阵，一个水平方向的均匀线阵和一个倾斜的均匀线阵，分别设为x轴和y轴，两个夹角可调节的均匀线阵都有M个阵元且阵元之间距离为d；K个窄带目标声源分别为S 1,S 2,L,S K，中心频率为f；声波入射方向与水平均匀线阵正轴方向的夹角为β,β∈(0,π)；
步骤二：建立两均匀线阵的信号接收模型；
当线阵夹角为α n时，K个窄带目标声源对应于水平线阵的方向角分别为θ nx1,θ nx2,...,θ nxK，对应于倾斜线阵的方向角分别为θ ny1,θ ny2,...,θ nyK；以第一个阵元为参考点，则第一个阵元在t时刻接收的信号为：
Figure PCTCN2018110446-appb-000001
其中s i(t)表示第i个源信号，n 1(t)表示第一个阵元上的噪声；
接收信号满足窄带条件，即当信号延迟远小于带宽倒数时，延迟作用相当于使基带信号产生一个相移，那么第m个阵元在同一时刻接收到的信号为：
Figure PCTCN2018110446-appb-000002
其中λ i表示第i个目标源反射回来的声波波长，n m(t)表示第m个阵元上的噪声；将各阵元的接收信号排列成列向量形式，则整个水平线阵接收的信号可用以下矢量式子表示：
X(t)＝AS(t)+N(t)          (1)
其中，
Figure PCTCN2018110446-appb-000003
为M×K的导向矢量矩阵，X(t)＝[x 1(t),x 2(t),L,x M(t)] T为M×1的接收信号矩阵，S(t)＝[s 1(t),s 2(t),L,s K(t)] T为K×1的源信号矩阵，N(t)＝[n 1(t),n 2(t),L,n M(t)] T为M×1的噪声矩阵。同理可得出倾斜均匀线阵的信号接收模型；
步骤三：建立均匀线阵子阵列模型，推导旋转算子Φ x和Φ y表达式；
将水平线阵中的M个阵元分为两个平移矢量为d的子阵列Z hx和Z hy；子阵列Z hx由水平阵列的第一到第M-1个阵元组成，则有：
x h1(t)＝x 1(t),x h2(t)＝x 2(t),L,x h(M-1)(t)＝x M-1(t)
其中，x h1(t),x h2(t),L,x h(M-1)(t)分别是子阵列Z hx上第一个阵元到第M-1个阵元接收到的信号；
子阵列Z hy由水平阵列的第二到第M个阵元组成，则有：
y h1(t)＝x 2(t),y h2(t)＝x 3(t),L,y h(M-1)(t)＝x M(t)
其中，y h1(t),y h2(t),L,y h(M-1)(t)分别是子阵列Z hy上第一个阵元到第M-1个阵元接收到的信号；
那么两个子阵列中第m个阵元的接收信号分别为：
Figure PCTCN2018110446-appb-000004
Figure PCTCN2018110446-appb-000005
其中
Figure PCTCN2018110446-appb-000006
n hxm(t)和n hym(t)分别为子阵Z hx和Z hy上第m个阵元的加性噪声，将上式写成矢量形式：
X h(t)＝AS(t)+N hx(t)
Y h(t)＝AΦ xS(t)+N hy(t)
其中矩阵Φ x为K×K的对角矩阵，它是把子阵Z hx和Z hy的输出联系起来的酉阵，也称旋转算子，其对角元素包含了K个信号的波前在任意一个阵元偶之间的相位延迟信息，表示为：
Figure PCTCN2018110446-appb-000007
根据以上步骤，同理可以将倾斜均匀线阵分为两个子阵列Z vx和Z vy，得到接收信号X v(t)和Y v(t)，从而得出旋转算子为：
Figure PCTCN2018110446-appb-000008
步骤四：建立旋转算子Φ x、Φ y与θ nxi、θ nyi之间的关系；
步骤五：建立声波信号从不同区域入射时两个方向角之间的关系；
步骤六：对矩阵Φ x和矩阵Φ y上的对角元素进行配对；
步骤七：根据配对结果求出θ nxi的大小。
优选的，步骤四具体包括：
X h(t)的协方差矩阵可以表示为：
R hxx＝E[X h(t)X h H(t)]＝AR ssA H+σ 2I
其中R ss＝E{S(t)S H(t)}，为信源部分协方差矩阵；
X h(t)和Y h(t)的互协方差矩阵为：
R hxy＝E{X h(t)Y h H(t)}＝AR ssΦ x HA H+σ 2Z
对矩阵协方差矩阵进行特征值分解得到最小特征值为σ 2，利用σ 2可以得到矩阵束{C hxx,C hxy}，其中
Figure PCTCN2018110446-appb-000009
C hxy＝R hxy-σ 2Z＝AR ssΦ x HA H；计算矩阵束{C hxx,C hxy}的广义特征值分解，得到非零特征值λ x1,λ x2,L,λ xK,它们一一对应着矩阵Φ x对角线上的元素，但对应关系并不确定，因此由公式(2)可记：
Figure PCTCN2018110446-appb-000010
其中φ xi为矩阵Φ x上的对角元素，且φ xi∈{λ x1,λ x2,L,λ xK},i＝1,2,L,K；
根据以上步骤，同理可以求得倾斜均匀阵列的两个协方差矩阵R vxx和R vxy，然后对矩阵束{C vxx,C vxy}进行特征值分解得到特征值λ y1,λ y2,L,λ yK，它们同样一一对应着矩阵Φ y上的对角元素，但对应关系同样不确定，由公式(3)可记：
Figure PCTCN2018110446-appb-000011
其中φ yi为矩阵Φ y上的对角元素，且φ yi∈{λ y1,λ y2,L,λ yK},i＝1,2,L,K。
优选的，步骤五的具体包括：
根据线阵夹角α n以及声波入射方向与x轴正轴方向的夹角β将声波信号入射区域设为4个：当β∈(0,α n)时，声波信号为区域1入射；当β∈(α n,π/2)时，声波信号为区域2入射；当β∈(π/2,π/2+α n)时，声波信号为区域3入射；当β∈(π/2+α n,π)时，声波信号为区域4入射；
(1)当声波从区域1入射时，θ 1i为声波入射方向与水平线阵法线的夹角，θ 1j为声波入射方向与倾斜线阵法线的夹角，此时有θ 1i+θ 1j＝π-α n；由于处在x轴上的阵列信号是以处在x轴最负方向的阵元为参考阵元的，并且子阵Z hx也在子阵Z hy的负x轴方向，因此当声波从区域1中入射时，参考阵元是最晚接收到信号的，子阵Z hx中的阵元也比子阵Z hy中对应的阵元晚接收到信号，从而可以得到时延参数τ小于0，又因为
Figure PCTCN2018110446-appb-000012
所以此时有θ nxi＝-θ 1i，同理有θ nyi＝-θ 1j；综上可得出：
θ nyi＝-θ nxi+α n-π           (6)
(2)当声波从区域2入射时，θ 2i为声波入射方向与水平线阵法线的夹角，θ 2j为声波入射方向与倾斜线阵法线的夹角，此时有θ 2j-θ 2i＝α n，根据(1)中所用分析方法，此时有θ nxi＝-θ 2i，θ nyi＝-θ 2j，综上可得出：
θ nyi＝θ nxi-α n            (7)
(3)当声波从区域3入射时，θ 3i为声波入射方向与水平线阵法线的夹角，θ 3j为声波入射方向与倾斜线阵法线的夹角，此时有θ 3i+θ 3j＝α n，根据(1)中所用分析方法，此时有θ nxi＝θ 3i，θ nyi＝-θ 3j，综上同样可得出：
θ nyi＝θ nxi-α n
(4)当声波从区域4入射时，θ 4i为声波入射方向与水平线阵法线的夹角，θ 4j为声波入射方向与倾斜线阵法线的夹角，此时有θ 4i-θ 4j＝α n，根据(1)中所用分析方法，此时有θ nxi＝θ 4i，θ nyi＝θ 4j，综上同样可得出：
θ nyi＝θ nxi-α n
根据公式(6)和公式(7)可以得到：
sinθ nyi＝sin(θ nxi-α n)             (8)
将公式(8)带入公式(5)，则有：
Figure PCTCN2018110446-appb-000013
优选的，步骤六具体包括：
根据公式(4)和公式(9)可知，若配对成功，则有以下式子成立：
Figure PCTCN2018110446-appb-000014
将arg(λ x1),arg(λ x2),L,arg(λ xK)按照各自的平方大小顺序从大到小排列得到序列Η；将arg(λ y1),arg(λ y2),L,arg(λ yK)按照各自的平方大小顺序从小到大排列得到序列V；于是有：
Figure PCTCN2018110446-appb-000015
其中h i为序列Η中的第i个元素；v i为序列V中的第i个元素。
优选的，步骤七中，
Figure PCTCN2018110446-appb-000016
优选的，改变两均匀线阵之间的夹角α n,n＝1,2,...,N，重复步骤一至步骤七；对于不同的线阵夹角α n，由公式(12)求出对应的波达方向角，最后对N个结果取平均值得出最终结果θ xi,i＝1,2,...,K。
一种基于可调夹角均匀线阵的水下波达方向估计装置，包括数据处理与控制模块、角度控制模块、发射模块、接收模块、输出模块和电源模块；电源模块与数据处理与控制模块、角度控制模块、发射模块、接收模块和输出模块相连，它能够为这些模块供电；
数据处理与控制模块是整个装置的核心部分，其它所有模块都与它直接相连；它可以控制发射模块，使发射模块发射指定的信号；可以控制角度控制模块，使两均匀线阵的夹角转至设定值；还能够对接收模块传过来的信号进行处理，计算出波达方向角，然后将结果传输至发射模块。
优选的，数据处理与控制模块由一对A/D、D/A转换器和一个处理器组成。
优选的，角度控制模块包括一个步进电机和驱动电路，用来控制两线阵之间的夹角；步进电机是将电脉冲信号转变为角位移或线位移的开环控制电机，当驱动电路收到一个脉冲信号，它就驱动步进电机按设定的方向转动固定的角度，可以通过使数据处理与控制模块发射一定数量的脉冲信号来达到期望的角度值。
优选的，接收模块包括两个超声波接收探头阵列，两阵列之间的夹角是可变的并且夹角可以通过角度控制模块进行调节。
具体的，水平阵列L1和步进电机固定在一起，阵列L2安装到步进电机上并且保证阵列L1和阵列L2在同一平面上，阵列L2可由步进电机带动旋转，从而达到两线阵夹角调节的目的。
具体的，在阵列L1末端有一个的固定支架，固定支架采用塑料材质；步进电机定子连接在此支架上，步进电机转子连接阵列L2。
优选的，发射模块包括一个阻抗匹配电路和一个超声波发射探头。
优选的，输出模块包括一个USB接口和一个显示器，它能够提供人机交互，将数据处理与控制模块中处理好的数据通过USB接口输出到外部装置或者在显示器上显示出来。
本发明与现有技术相比，具有如下优点和有益效果：
1、本发明与利用传统ESPRIT算法进行水下目标波达方向估计的方法相比更具有实用性，估计精确度也更高。传统的ESPRIT算法通常假定声速为一个常量，而在实际的复杂水下环境中，声速往往是不断变化的，如果把其当成一个常量来进行计算的话，会导致较大的误差。本发明采用两个夹角可以调节的均匀线阵，通过两个阵列夹角与波达方向角之间的关系消去了声速这个变量，使得最后的运算结果与声速无关，从而提高了估计精度，同时由于两线阵夹角可变，通过取不同值进行多次测量，可以更好的消除误差。
2、本发明在传统ESPRIT算法上进行了改进，同时保留了ESPRIT算法分辨率高的优点，并且改进后算法的运算量和复杂度没有过多增加，保证了算法的可行性。
3、本发明装置在传统的测量装置上进行了改进，使用夹角可调剂的均匀线阵，可行性强，安装简单。除此之外，现代处理器计算处理能力的不断提高，这使得本发明所使用的处理器等芯片的集成度高，并且计算能力强，从而保证了本发明的可行性。
附图说明
图1为实施例装置的硬件结构模块图。
图2为接收模块连接示意图。
图3为接收模块连接俯视图。
图4为接收模块连接侧视图。
图5为实施例所用的可调夹角均匀线阵模型。
图6为水平均匀线阵的接收信号模型。
图7为信号从区域1入射时的可调夹角均匀线阵模型。
图8为信号从区域2入射时的可调夹角均匀线阵模型。
图9为信号从区域3入射时的可调夹角均匀线阵模型。
图10为信号从区域4入射时的可调夹角均匀线阵模型。
图11为实施例方法的流程图。
具体实施方式
下面结合实施例及附图对本发明作进一步详细的描述，但本发明的实施方式不限于此。
实施例1
一种基于可调夹角均匀线阵的水下波达方向估计方法，通过对两个线阵的接收信号进行处理，在波达方向估计中可以消去声速这个因子，从而消除水下声速不确定性对目标定位精度的影响。其次由于两均匀线阵夹角可变，在实际测量中可以改变夹角进行多次测量，更好地消除误差。
本方法采用两个夹角可调节的均匀线阵，两线阵都有M个阵元且阵元之间距离为d；K个窄带目标声源分别为S 1,S 2,L,S K，中心频率为f；声波入射方向与水平均匀线阵正轴方向的夹角为β,β∈(0,π)；本方法将测量N次不同的线阵夹角值α n,n＝1,2,...,N且α n∈(0,π/2)，具体步骤如下：
步骤一：建立夹角可调均匀线阵模型，如图5所示。在水中放置两个夹角为α n的均匀线阵，一个水平方向的均匀线阵和一个倾斜的均匀线阵，分别设为x轴和y轴。根据线阵夹角α n以及声波入射方向与x轴正轴方向的夹角β将声波信号入射区域设为4个：当β∈(0,α n)时，声波信号为区域1入射；当β∈(α n,π/2)时，声波信号为区域2入射；当β∈(π/2,π/2+α n)时，声波信号为区域3入射；当β∈(π/2+α n,π)时，声波信号为区域4入射；
步骤二：建立两均匀线阵的信号接收模型。当线阵夹角为α n时，K个窄带目标声源对应于水平线阵的方向角分别为θ nx1,θ nx2,...,θ nxK，对应于倾斜线阵的方向角分别为θ ny1,θ ny2,...,θ nyK。水平均匀线阵的模型场景如图6所示。以第一个阵元为参考点，则第一个阵元在t时刻接收的信号为：
Figure PCTCN2018110446-appb-000017
其中s i(t)表示第i个源信号，n 1(t)表示第一个阵元上的噪声。
接收信号满足窄带条件，即当信号延迟远小于带宽倒数时，延迟作用相当于使基带信号产生一个相移。那么第m个阵元在同一时刻接收到的信号为：
Figure PCTCN2018110446-appb-000018
其中λ i表示第i个目标源反射回来的声波波长，n m(t)表示第m个阵元上的噪声。将各阵元的接收信号排列成列向量形式，则整个水平线阵接收的信号可用以下矢量式子表示：
X(t)＝AS(t)+N(t)          (1)
其中，
Figure PCTCN2018110446-appb-000019
为M×K的导向矢量矩阵，X(t)＝[x 1(t),x 2(t),L,x M(t)] T为M×1的接收信号矩阵，S(t)＝[s 1(t),s 2(t),L,s K(t)] T为K×1的源信号矩阵，N(t)＝[n 1(t),n 2(t),L,n M(t)] T为M×1的噪声矩阵。同理可得出倾斜均匀线阵的信号接收模型。
步骤三：建立均匀线阵子阵列模型，推导旋转算子表达式。将水平线阵中的M个阵元分为两个平移矢量为d的子阵列Z hx和Z hy。子阵列Z hx由水平阵列的第一到第M-1个阵元组成，则有：
x h1(t)＝x 1(t),x h2(t)＝x 2(t),L,x h(M-1)(t)＝x M-1(t)
其中，x h1(t),x h2(t),L,x h(M-1)(t)分别是子阵列Z hx上第一个阵元到第M-1个阵元接收到的信号。
子阵列Z hy由水平阵列的第二到第M个阵元组成，则有：
y h1(t)＝x 2(t),y h2(t)＝x 3(t),L,y h(M-1)(t)＝x M(t)
其中，y h1(t),y h2(t),L,y h(M-1)(t)分别是子阵列Z hy上第一个阵元到第M-1个阵元接收到的信号。
那么两个子阵列中第m个阵元的接收信号分别为：
Figure PCTCN2018110446-appb-000020
Figure PCTCN2018110446-appb-000021
其中
Figure PCTCN2018110446-appb-000022
n hxm(t)和n hym(t)分别为子阵Z hx和Z hy上第m个阵元的加性噪声。将上式写成矢量形式：
X h(t)＝AS(t)+N hx(t)
Y h(t)＝AΦ xS(t)+N hy(t)
其中矩阵Φ x为K×K的对角矩阵，它是把子阵Z hx和Z hy的输出联系起来的酉阵，也称旋转算子，其对角元素包含了K个信号的波前在任意一个阵元偶之间的相位延迟信息，表示为：
Figure PCTCN2018110446-appb-000023
根据以上步骤，同理可以将倾斜均匀线阵分为两个子阵列Z vx和Z vy，得到接收信号X v(t)和Y v(t)，从而得出旋转算子为：
Figure PCTCN2018110446-appb-000024
步骤四：建立旋转算子Φ x和Φ y与θ nxi和θ nyi之间的关系。X h(t)的协方差矩阵可以表示为：
R hxx＝E[X h(t)X h H(t)]＝AR ssA H+σ 2I
其中R ss＝E{S(t)S H(t)}，为信源部分协方差矩阵。
X h(t)和Y h(t)的互协方差矩阵为：
R hxy＝E{X h(t)Y h H(t)}＝AR ssΦ x HA H+σ 2Z
对矩阵协方差矩阵进行特征值分解得到最小特征值为σ 2，利用σ 2可以得到矩阵束{C hxx,C hxy}，其中
Figure PCTCN2018110446-appb-000025
C hxy＝R hxy-σ 2Z＝AR ssΦ x HA H。计算矩阵束{C hxx,C hxy}的广义特征值分解，得到非零特征值λ x1,λ x2,L,λ xK,它们一一对应着矩阵Φ x对角线上的元素，但对应关系并不确定，因此由公式(2)可记：
Figure PCTCN2018110446-appb-000026
其中φ xi为矩阵Φ x上的对角元素，且φ xi∈{λ x1,λ x2,L,λ xK},i＝1,2,L,K。
根据以上步骤，同理可以求得倾斜均匀阵列的两个协方差矩阵R vxx和R vxy，然后对矩阵束{C vxx,C vxy}进行特征值分解得到特征值λ y1,λ y2,L,λ yK，它们同样一一对应着矩阵Φ y上的对角元素，但对应关系同样不确定，由公式(3)可记：
Figure PCTCN2018110446-appb-000027
其中φ yi为矩阵Φ y上的对角元素，且φ yi∈{λ y1,λ y2,L,λ yK},i＝1,2,L,K。
步骤五：建立声波信号从不同区域入射时两个方向角之间的关系。
(1)当声波从区域1入射时，如图7所示，θ 1i为声波入射方向与水平线阵法线的夹角，θ 1j为声波入射方向与倾斜线阵法线的夹角，此时有θ 1i+θ 1j＝π-α n。由于处在x轴上的阵列信号是以处在x轴最负方向的阵元为参考阵元的，并且子阵Z hx也在子阵Z hy的负x轴方向。 因此当声波从区域1中入射时，参考阵元是最晚接收到信号的，子阵Z hx中的阵元也比子阵Z hy中对应的阵元晚接收到信号，从而可以得到时延参数τ小于0，又因为
Figure PCTCN2018110446-appb-000028
所以此时有θ nxi＝-θ 1i，同理有θ nyi＝-θ 1j。综上可得出：
θ nyi＝-θ nxi+α n-π             (6)
(2)当声波从区域2入射时，如图8所示，θ 2i为声波入射方向与水平线阵法线的夹角，θ 2j为声波入射方向与倾斜线阵法线的夹角，此时有θ 2j-θ 2i＝α n，根据(1)中所用分析方法，此时有θ nxi＝-θ 2i，θ nyi＝-θ 2j，综上可得出：
θ nyi＝θ nxi-α n            (7)
(3)当声波从区域3入射时，如图9所示，θ 3i为声波入射方向与水平线阵法线的夹角，θ 3j为声波入射方向与倾斜线阵法线的夹角，此时有θ 3i+θ 3j＝α n，根据(1)中所用分析方法，此时有θ nxi＝θ 3i，θ nyi＝-θ 3j，综上同样可得出：
θ nyi＝θ nxi-α n
(4)当声波从区域4入射时，如图10所示，θ 4i为声波入射方向与水平线阵法线的夹角，θ 4j为声波入射方向与倾斜线阵法线的夹角，此时有θ 4i-θ 4j＝α n，根据(1)中所用分析方法，此时有θ nxi＝θ 4i，θ nyi＝θ 4j，综上同样可得出
θ nyi＝θ nxi-α n
根据公式(6)和公式(7)可以得到：
sinθ nyi＝sin(θ nxi-α n)            (8)
将公式(8)带入公式(5)，则有：
Figure PCTCN2018110446-appb-000029
步骤六：对矩阵Φ x和矩阵Φ y上的对角元素φ xi与φ yi进行配对。根据公式(4)和公式(9)可知，若配对成功，则有以下式子成立：
Figure PCTCN2018110446-appb-000030
将arg(λ x1),arg(λ x2),L,arg(λ xK)按照各自的平方大小顺序从大到小排列得到序列Η；将arg(λ y1),arg(λ y2),L,arg(λ yK)按照各自的平方大小顺序从小到大排列得到序列V。于是有：
Figure PCTCN2018110446-appb-000031
其中h i为序列Η中的第i个元素；v i为序列V中的第i个元素。
步骤七：根据配对结果求出θ nxi的大小。
根据公式(10)可以得出：
Figure PCTCN2018110446-appb-000032
步骤八：改变两均匀线阵之间的夹角α n,n＝1,2,...,N，重复步骤1至步骤7。对于不同的线阵夹角α n，由公式12求出对应的波达方向角，最后对N个结果取平均值得出最终结果θ xi,i＝1,2,...,K。
根据以上算法流程可知，本实施例提出的改进算法不需要知道声速的大小就可以对θ xi进行精确的估计，即可以在声速不确定的情况下估计出波达方向角θ xi的值，克服了传统ESPRIT算法的缺点。同时通过改变两线阵之间的夹角进行多次估计最后取平均值，可以有效地消除误差。
以上方法的流程图可以由图11表示。
实施例2
本实施例提供的基于可调夹角均匀线阵的水下波达方向估计装置如图1所示，包括数据处理与控制模块、角度控制模块、发射模块、接收模块、输出模块和电源模块。
数据处理与控制模块由一对A/D、D/A转换器和一个处理器组成，是整个装置的核心部分，其它所有模块都与它直接相连。它可以控制发射模块，使发射模块发射指定的信号；可以控制角度控制模块，使两均匀线阵的夹角转至设定值；还能够对接收模块传过来的信号进行处理，通过实施例1的算法计算出波达方向角，然后将结果传输至发射模块。
角度控制模块用来控制两线阵之间的夹角，由一个步进电机和驱动电路组成。步进电机是将电脉冲信号转变为角位移或线位移的开环控制电机，当驱动电路收到一个脉冲信号，它就驱动步进电机按设定的方向转动固定的角度，称为步距角。所以可以通过使数据处理与控制模块发射一定数量的脉冲信号来达到期望的角度值。
接收模块由两个超声波接收探头阵列组成，两阵列之间的夹角是可变的并且夹角可以通过角度控制模块进行调节，如图2所示，水平阵列L1和步进电机固定在一起，阵列L2安装到步进电机上并且保证阵列L1和阵列L2在同一平面上，阵列L2可由步进电机带动旋转，从而达到两线阵夹角调节的目的。图3和图4分别为装置连接俯视图和侧视图，如图所示，在阵列L1末端有一个的固定支架，因为接收模块会放置在水中，所以固定支架采用塑料材质以增大浮力。步进电机定子连接在此支架上，步进电机转子连接阵列L2。两阵列还能接收从目标声源发射回来的信号，然后将其进行A/D转换后传送至处理器。
发射模块由一个阻抗匹配电路和一个超声波发射探头组成，通过D/A转换器与处理器相连，能够根据处理器发出的指令发射指定的信号。
输出模块由一个USB接口和一个显示器组成，并且与数据处理与控制模块和电源模块相连。它能够提供人机交互，将数据处理与控制模块中处理好的数据通过USB接口输出到外部装置或者在显示器上显示出来。
电源模块由一个电源组成，并且与数据处理与控制模块、角度控制模块、发射模块、接收模块和输出模块相连。它能够为这些模块供电。
本装置的主要工作流程如下：在实测过程中根据想要发射的信号参数，通过数据处理与控制模块输入对应的参数，使处理器产生相应的数字信号，然后通过D/A转换后传给发射模块，超声波发射探头就能产生我们需要的信号并进行发射。两线阵之间的夹角值可以通过数据处理与控制模块进行设定，处理器发送特定的脉冲信号到角度控制模块的驱动电路，然后驱动电路就可以驱动步进电机转动至需要的角度。接收模块中的接收阵列收到从目标声源反射回来的信号后将其通过A/D转换成数字信号后发送给处理器，然后处理器根据提供的算法计算出结果。最后数据处理与控制模块将计算结果传给输出模块，输出模块将结果通过USB接口传给外部设备或者通过显示器显示出来。电源模块为所有其它模块供电。
本装置包括数据处理与控制模块、角度控制模块、发射模块、接收模块、输出模块和电源模块。数据处理与控制模块可以用DSP芯片实现(如：TI公司TMS320VC5509A型号的DSP芯片)，此DSP芯片可实现A/D转换和D/A转换的功能，并能够实现均匀线阵的旋转算子和最终波达方向的计算；角度控制模块包括步进电机和驱动电路，采用富兴公司HSTM42-1.8-D-26-4-0.4型号的步进电机，此步进电机的步距角为1.8度，驱动电路采用ULN2003芯片；发射模块使用一个超声波发射探头；接收模块使用两个可调夹角的均匀直线阵列，其中每个阵列包括多个超声接收探头，并且数量相同，两线阵按图2所示组装；输出模块使用一个USB接口和一个LCD显示屏。图1即为本发明所述装置的硬件结构模块图。
工作步骤具体如下：
步骤1：设置5个不同的线阵夹角值，即取N＝5，分别为15°，30°，45°，60°，75°。在数据处理与控制模块设定线阵夹角值，通过角度控制模块将两线阵夹角转为15°。在水下放置4个目标声源，与水平阵列法线的夹角分别为30°，60°，-30°，-60°。通过数据处理与控制模块设置发射模块的参数，使其发射信号的频率为100kHz,脉冲长度5ms。设置接收阵列参数，将两均匀线阵各自的阵元个数M定为10，阵元之间距离d设为5mm，则前9个阵元为一子阵，后9个阵元为另一子阵，两子阵之间距离为d。
步骤2：对超声接收探头接收到的目标声源信号进行采样；水平方向均匀阵列接收到的信号分别为x x1(t),x x2(t),L,x x8(t)和y x1(t),y x2(t),L,y x8(t)，倾斜方向均匀阵列接收的信号分别为x y1(t),x y2(t),L,x y8(t)和y y1(t),y y2(t),L,y y8(t)。共采样接收200次，并将接收到的信号传递给数据采集处理与控制模块做运算处理。
步骤3：信号在数据采集处理与控制模块中的处理步骤具体如下：
1)将处在水平方向上的均匀阵列接收到的信号排成矢量形式X h(t)和Y h(t)，计算X h(t)的协方差矩阵R hxx＝E[X h(t)X h H(t)]，X h(t)和Y h(t)之间的互协方差矩阵R hxy＝E{X h(t)Y h H(t)}。同时对倾斜方向上的均匀阵列接收到的信号也进行相同处理，得到R vxx＝E[X v(t)X v H(t)]和R vxy＝E{X v(t)Y v H(t)}
2)对水平阵列中的两个协方差矩阵R hxx和R hxy进行特征值分解，得到最小的特征值σ 2，从而有C hxx＝R hxx-σ 2I＝AR ssA H和C hxy＝R hxy-σ 2Z＝AR ssΦ HA H。同时对倾斜阵列中的两个协方差矩阵进行相同的处理，得到C vxx和C vxy。
3)分别计算矩阵束{C hxx,C hxy}和{C vxx,C vxy}的广义特征值分解，得到λ x1,λ x2,L,λ xK和λ y1,λ y2,L,λ yK。
4)将arg(λ x1),arg(λ x2),L,arg(λ xK)按照各自的平方大小顺序从大到小排列得到序列Η，将arg(λ y1),arg(λ y2),L,arg(λ yK)按照各自的平方大小顺序从小到大排列得到序列V。然后把H中第i个元素h i的值赋给arg(φ xi)，V中第i个元素v i的值赋给arg(φ yi)。
5)根据匹配得出的arg(φ xi)和arg(φ yi)以及两线阵之间的夹角最终求得：
Figure PCTCN2018110446-appb-000033
步骤4：将计算出的方向角信息存储下来，并传送给输出模块，使其通过USB接口输出给外部装置或者显示在LCD显示屏上。
步骤5：改变两线阵之间的夹角，分别设为30°，45°，60°，75°根据每次计算出来的结果最后取平均值，根据算法估计出的方向角分别为30°，60°，-30°，-60°，与实际角度相同，说明估计结果正确，本方法及装置可行。
上述实施例为本发明较佳的实施方式，但本发明的实施方式并不受上述实施例的限制，其他的任何未背离本发明的精神实质与原理下所作的改变、修饰、替代、组合、简化，均应为等效的置换方式，都包含在本发明的保护范围之内。

Claims (10)

  1. 基于可调夹角均匀线阵的水下波达方向估计方法，其特征在于，包括以下步骤：
    步骤一：建立夹角可调均匀线阵模型；
    在水中放置两个夹角为α n的均匀线阵，一个水平方向的均匀线阵和一个倾斜的均匀线阵，分别设为x轴和y轴，两个夹角可调节的均匀线阵都有M个阵元且阵元之间距离为d；K个窄带目标声源分别为S 1,S 2,L,S K，中心频率为f；声波入射方向与水平均匀线阵正轴方向的夹角为β,β∈(0,π)；
    步骤二：建立两均匀线阵的信号接收模型；
    当线阵夹角为α n时，K个窄带目标声源对应于水平线阵的方向角分别为θ nx1,θ nx2,...,θ nxK，对应于倾斜线阵的方向角分别为θ ny1,θ ny2,...,θ nyK；以第一个阵元为参考点，则第一个阵元在t时刻接收的信号为：
    Figure PCTCN2018110446-appb-100001
    其中s i(t)表示第i个源信号，n 1(t)表示第一个阵元上的噪声；
    接收信号满足窄带条件，即当信号延迟远小于带宽倒数时，延迟作用相当于使基带信号产生一个相移，那么第m个阵元在同一时刻接收到的信号为：
    Figure PCTCN2018110446-appb-100002
    其中λ i表示第i个目标源反射回来的声波波长，n m(t)表示第m个阵元上的噪声；将各阵元的接收信号排列成列向量形式，则整个水平线阵接收的信号可用以下矢量式子表示：
    X(t)＝AS(t)+N(t)          (1)
    其中，
    Figure PCTCN2018110446-appb-100003
    为M×K的导向矢量矩阵，X(t)＝[x 1(t),x 2(t),L,x M(t)] T为M×1的接收信号矩阵，S(t)＝[s 1(t),s 2(t),L,s K(t)] T为K×1的源信号矩阵，N(t)＝[n 1(t),n 2(t),L,n M(t)] T为M×1的噪声矩阵；同理可得出倾斜均匀线阵的信号接收模型；
    步骤三：建立均匀线阵子阵列模型，推导旋转算子Φ x和Φ y表达式；
    将水平线阵中的M个阵元分为两个平移矢量为d的子阵列Z hx和Z hy；子阵列Z hx由水平阵列的第一到第M-1个阵元组成，则有：
    x h1(t)＝x 1(t),x h2(t)＝x 2(t),L,x h(M-1)(t)＝x M-1(t)
    其中，x h1(t),x h2(t),L,x h(M-1)(t)分别是子阵列Z hx上第一个阵元到第M-1个阵元接收到的信号；
    子阵列Z hy由水平阵列的第二到第M个阵元组成，则有：
    y h1(t)＝x 2(t),y h2(t)＝x 3(t),L,y h(M-1)(t)＝x M(t)
    其中，y h1(t),y h2(t),L,y h(M-1)(t)分别是子阵列Z hy上第一个阵元到第M-1个阵元接收到的信号；
    那么两个子阵列中第m个阵元的接收信号分别为：
    Figure PCTCN2018110446-appb-100004
    Figure PCTCN2018110446-appb-100005
    其中
    Figure PCTCN2018110446-appb-100006
    n hxm(t)和n hym(t)分别为子阵Z hx和Z hy上第m个阵元的加性噪声，将上式写成矢量形式：
    X h(t)＝AS(t)+N hx(t)
    Y h(t)＝AΦ xS(t)+N hy(t)
    其中矩阵Φ x为K×K的对角矩阵，它是把子阵Z hx和Z hy的输出联系起来的酉阵，也称旋转算子，其对角元素包含了K个信号的波前在任意一个阵元偶之间的相位延迟信息，表示为：
    Figure PCTCN2018110446-appb-100007
    根据以上步骤，同理可以将倾斜均匀线阵分为两个子阵列Z vx和Z vy，得到接收信号X v(t)和Y v(t)，从而得出旋转算子为：
    Figure PCTCN2018110446-appb-100008
    步骤四：建立旋转算子Φ x、Φ y与θ nxi、θ nyi之间的关系；
    步骤五：建立声波信号从不同区域入射时两个方向角之间的关系；
    步骤六：对矩阵Φ x和矩阵Φ y上的对角元素进行配对；
    步骤七：根据配对结果求出θ nxi的大小。
  2. 根据权利要求1所述的基于可调夹角均匀线阵的水下波达方向估计方法，其特征在于，步骤四具体包括：
    X h(t)的协方差矩阵可以表示为：
    R hxx＝E[X h(t)X h H(t)]＝AR ssA H+σ 2I
    其中R ss＝E{S(t)S H(t)}，为信源部分协方差矩阵；
    X h(t)和Y h(t)的互协方差矩阵为：
    R hxy＝E{X h(t)Y h H(t)}＝AR ssΦ x HA H+σ 2Z
    对矩阵协方差矩阵进行特征值分解得到最小特征值为σ 2，利用σ 2可以得到矩阵束{C hxx,C hxy}，其中
    Figure PCTCN2018110446-appb-100009
    C hxy＝R hxy-σ 2Z＝AR ssΦ x HA H；计算矩阵束{C hxx,C hxy}的广义特征值分解，得到非零特征值λ x1,λ x2,L,λ xK,它们一一对应着矩阵Φ x对角线上的元素，但对应关系并不确定，因此由公式(2)可记：
    Figure PCTCN2018110446-appb-100010
    其中φ xi为矩阵Φ x上的对角元素，且φ xi∈{λ x1,λ x2,L,λ xK},i＝1,2,L,K；
    根据以上步骤，同理可以求得倾斜均匀阵列的两个协方差矩阵R vxx和R vxy，然后对矩阵束{C vxx,C vxy}进行特征值分解得到特征值λ y1,λ y2,L,λ yK，它们同样一一对应着矩阵Φ y上的对角元素，但对应关系同样不确定，由公式(3)可记：
    Figure PCTCN2018110446-appb-100011
    其中φ yi为矩阵Φ y上的对角元素，且φ yi∈{λ y1,λ y2,L,λ yK},i＝1,2,L,K。
  3. 根据权利要求2所述的基于可调夹角均匀线阵的水下波达方向估计方法，其特征在于，步骤五的具体包括：
    根据线阵夹角α n以及声波入射方向与x轴正轴方向的夹角β将声波信号入射区域设为4个：当β∈(0,α n)时，声波信号为区域1入射；当β∈(α n,π/2)时，声波信号为区域2入射；当β∈(π/2,π/2+α n)时，声波信号为区域3入射；当β∈(π/2+α n,π)时，声波信号为区域4入射；
    (1)当声波从区域1入射时，θ 1i为声波入射方向与水平线阵法线的夹角，θ 1j为声波入射方向与倾斜线阵法线的夹角，此时有θ 1i+θ 1j＝π-α n；由于处在x轴上的阵列信号是以处在x轴最负方向的阵元为参考阵元的，并且子阵Z hx也在子阵Z hy的负x轴方向，因此当声波从区域1中入射时，参考阵元是最晚接收到信号的，子阵Z hx中的阵元也比子阵Z hy中对应的阵元晚接收到信号，从而可以得到时延参数τ小于0，又因为
    Figure PCTCN2018110446-appb-100012
    所以此时有θ nxi＝-θ 1i，同理有θ nyi＝-θ 1j；综上可得出：
    θ nyi＝-θ nxi+α n-π         (6)
    (2)当声波从区域2入射时，θ 2i为声波入射方向与水平线阵法线的夹角，θ 2j为声波入射方向与倾斜线阵法线的夹角，此时有θ 2j-θ 2i＝α n，根据(1)中所用分析方法，此时有θ nxi＝-θ 2i，θ nyi＝-θ 2j，综上可得出：
    θ nyi＝θ nxi-α n           (7)
    (3)当声波从区域3入射时，θ 3i为声波入射方向与水平线阵法线的夹角，θ 3j为声波入射方向与倾斜线阵法线的夹角，此时有θ 3i+θ 3j＝α n，根据(1)中所用分析方法，此时有θ nxi＝θ 3i，θ nyi＝-θ 3j，综上同样可得出：
    θ nyi＝θ nxi-α n
    (4)当声波从区域4入射时，θ 4i为声波入射方向与水平线阵法线的夹角，θ 4j为声波入射方向与倾斜线阵法线的夹角，此时有θ 4i-θ 4j＝α n，根据(1)中所用分析方法，此时有θ nxi＝θ 4i，θ nyi＝θ 4j，综上同样可得出：
    θ nyi＝θ nxi-α n
    根据公式(6)和公式(7)可以得到：
    sinθ nyi＝sin(θ nxi-α n)            (8)
    将公式(8)带入公式(5)，则有：
    Figure PCTCN2018110446-appb-100013
  4. 根据权利要求3所述的基于可调夹角均匀线阵的水下波达方向估计方法，其特征在于，步骤六具体包括：
    根据公式(4)和公式(9)可知，若配对成功，则有以下式子成立：
    Figure PCTCN2018110446-appb-100014
    将arg(λ x1),arg(λ x2),L,arg(λ xK)按照各自的平方大小顺序从大到小排列得到序列Η；将arg(λ y1),arg(λ y2),L,arg(λ yK)按照各自的平方大小顺序从小到大排列得到序列V；于是有：
    Figure PCTCN2018110446-appb-100015
    其中h i为序列Η中的第i个元素；v i为序列V中的第i个元素。
  5. 根据权利要求4所述的基于可调夹角均匀线阵的水下波达方向估计方法，其特征在于，步骤七中，
    Figure PCTCN2018110446-appb-100016
    i＝1,2,...K。
  6. 根据权利要求5所述的基于可调夹角均匀线阵的水下波达方向估计方法，其特征在于，改变两均匀线阵之间的夹角α n,n＝1,2,...,N，重复步骤一至步骤七；对于不同的线阵夹角α n，由公式(12)求出对应的波达方向角，最后对N个结果取平均值得出最终结果θ xi,i＝1,2,...,K。
  7. 基于权利要求1所述方法的基于可调夹角均匀线阵的水下波达方向估计装置，其特征在于，包括数据处理与控制模块、角度控制模块、发射模块、接收模块、输出模块和电源模块；电源模块与数据处理与控制模块、角度控制模块、发射模块、接收模块和输出模块相连，它能够为这些模块供电；
    数据处理与控制模块是整个装置的核心部分，其它所有模块都与它直接相连；它可以控制发射模块，使发射模块发射指定的信号；可以控制角度控制模块，使两均匀线阵的夹角转至设定值；还能够对接收模块传过来的信号进行处理，计算出波达方向角，然后将结果传输至发射模块。
  8. 根据权利要求7所述的装置，其特征在于，角度控制模块包括一个步进电机和驱动电路，用来控制两线阵之间的夹角；步进电机是将电脉冲信号转变为角位移或线位移的开环控制电机，当驱动电路收到一个脉冲信号，它就驱动步进电机按设定的方向转动固定的角度，可以通过使数据处理与控制模块发射一定数量的脉冲信号来达到期望的角度值。
  9. 根据权利要求7所述的装置，其特征在于，接收模块包括两个超声波接收探头阵列，两阵列之间的夹角是可变的并且夹角可以通过角度控制模块进行调节；水平阵列L1和步进电机固定在一起，阵列L2安装到步进电机上并且保证阵列L1和阵列L2在同一平面上，阵列L2可由步进电机带动旋转，从而达到两线阵夹角调节的目的。
  10. 根据权利要求9所述的装置，其特征在于，在阵列L1末端有一个的固定支架，固定支架采用塑料材质；步进电机定子连接在此支架上，步进电机转子连接阵列L2。
PCT/CN2018/110446 2017-11-16 2018-10-16 基于可调夹角均匀线阵的水下波达方向估计方法及装置 WO2019095912A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201711137001.0A CN108008348B (zh) 2017-11-16 2017-11-16 基于可调夹角均匀线阵的水下波达方向估计方法及装置
CN201711137001.0 2017-11-16

Publications (1)

Publication Number Publication Date
WO2019095912A1 true WO2019095912A1 (zh) 2019-05-23

Family

ID=62052528

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/110446 WO2019095912A1 (zh) 2017-11-16 2018-10-16 基于可调夹角均匀线阵的水下波达方向估计方法及装置

Country Status (2)

Country Link
CN (1) CN108008348B (zh)
WO (1) WO2019095912A1 (zh)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112180327A (zh) * 2020-09-04 2021-01-05 西北工业大学 一种存在互耦条件下基于多普勒频移的直接定位方法
CN112230194A (zh) * 2020-08-05 2021-01-15 北京航空航天大学杭州创新研究院 一种基于平移阵列的解模糊方法、设备及存储介质
CN112698264A (zh) * 2020-12-10 2021-04-23 南京航空航天大学 增广互质阵列脉冲噪声环境下相干信源的doa估计方法
CN113030925A (zh) * 2021-03-24 2021-06-25 中国船舶重工集团公司第七一九研究所 一种数据采集设备、水下垂直阵阵元位置测量系统及方法
CN113376568A (zh) * 2021-05-14 2021-09-10 南京航空航天大学 一种基于子空间正交补偿的圆阵doa估计方法
CN114114149A (zh) * 2021-11-22 2022-03-01 北京航空航天大学 一种高精度多功能小型水下定位装置

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108008348B (zh) * 2017-11-16 2023-07-18 华南理工大学 基于可调夹角均匀线阵的水下波达方向估计方法及装置
CN108535682B (zh) * 2018-06-15 2023-09-29 华南理工大学 一种基于旋转非均匀双l阵的水下二维doa估计方法及装置
CN109405829A (zh) * 2018-08-28 2019-03-01 桂林电子科技大学 基于智能手机音视频多源信息融合的行人自定位方法
CN109521392B (zh) * 2018-10-24 2022-12-16 华南理工大学 基于非圆信号和l型线阵的水下一维doa估计方法和装置
CN109407048B (zh) * 2018-11-12 2023-09-29 华南理工大学 基于非圆信号和夹角可调阵的水下doa估计方法与装置
CN109581275B (zh) * 2018-12-13 2023-09-29 华南理工大学 基于非圆信号和三维正交阵的二维水下doa估计方法和装置
CN109581274B (zh) * 2018-12-13 2023-09-29 华南理工大学 基于夹角可调三维阵的非圆信号水下doa估计方法和装置
CN113866269A (zh) * 2021-09-16 2021-12-31 中国科学院南海海洋研究所 一种垂向横截面分层声学测量系统及方法

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20130034095A (ko) * 2011-09-28 2013-04-05 한국전자통신연구원 모바일 신호의 도착각/도착시간을 추정하는 장치 및 방법
CN105607033A (zh) * 2016-03-07 2016-05-25 华南理工大学 基于正交均匀线阵的水下波达方向估计方法及系统
CN105824002A (zh) * 2016-04-15 2016-08-03 西安电子科技大学 基于嵌套式子阵阵列的波达方向估计方法
CN106405487A (zh) * 2016-10-17 2017-02-15 重庆邮电大学 一种通用基于扩展esprit技术的空间谱估计方法
CN106443574A (zh) * 2016-11-08 2017-02-22 西安电子科技大学 基于双层嵌套阵列的波达方向角估计方法
CN107340495A (zh) * 2017-06-28 2017-11-10 西安电子科技大学 一种基于阵列雷达的目标波达方向快速估计方法
CN108008348A (zh) * 2017-11-16 2018-05-08 华南理工大学 基于可调夹角均匀线阵的水下波达方向估计方法及装置

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103049003B (zh) * 2012-10-19 2016-03-30 西安交通大学 一种基于平行均匀线阵的相干信号二维波达角度跟踪方法及装置
US20140152503A1 (en) * 2012-12-03 2014-06-05 Qualcomm Incorporated Direction of arrival estimation using linear array
CN104391268B (zh) * 2014-11-21 2017-10-13 哈尔滨工业大学深圳研究生院 一种波达方位角的检测方法
CN104730491B (zh) * 2015-03-06 2017-05-31 中国计量学院 一种基于l型阵的虚拟阵列doa估计方法
CN106500820B (zh) * 2016-10-13 2019-08-20 华南理工大学 一种用于二维波达方向估计的声速测量方法及装置

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20130034095A (ko) * 2011-09-28 2013-04-05 한국전자통신연구원 모바일 신호의 도착각/도착시간을 추정하는 장치 및 방법
CN105607033A (zh) * 2016-03-07 2016-05-25 华南理工大学 基于正交均匀线阵的水下波达方向估计方法及系统
CN105824002A (zh) * 2016-04-15 2016-08-03 西安电子科技大学 基于嵌套式子阵阵列的波达方向估计方法
CN106405487A (zh) * 2016-10-17 2017-02-15 重庆邮电大学 一种通用基于扩展esprit技术的空间谱估计方法
CN106443574A (zh) * 2016-11-08 2017-02-22 西安电子科技大学 基于双层嵌套阵列的波达方向角估计方法
CN107340495A (zh) * 2017-06-28 2017-11-10 西安电子科技大学 一种基于阵列雷达的目标波达方向快速估计方法
CN108008348A (zh) * 2017-11-16 2018-05-08 华南理工大学 基于可调夹角均匀线阵的水下波达方向估计方法及装置

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112230194A (zh) * 2020-08-05 2021-01-15 北京航空航天大学杭州创新研究院 一种基于平移阵列的解模糊方法、设备及存储介质
CN112230194B (zh) * 2020-08-05 2024-01-26 北京航空航天大学杭州创新研究院 一种基于平移阵列的解模糊方法、设备及存储介质
CN112180327A (zh) * 2020-09-04 2021-01-05 西北工业大学 一种存在互耦条件下基于多普勒频移的直接定位方法
CN112180327B (zh) * 2020-09-04 2024-04-09 西北工业大学 一种存在互耦条件下基于多普勒频移的直接定位方法
CN112698264A (zh) * 2020-12-10 2021-04-23 南京航空航天大学 增广互质阵列脉冲噪声环境下相干信源的doa估计方法
CN112698264B (zh) * 2020-12-10 2023-12-05 南京航空航天大学 增广互质阵列脉冲噪声环境下相干信源的doa估计方法
CN113030925A (zh) * 2021-03-24 2021-06-25 中国船舶重工集团公司第七一九研究所 一种数据采集设备、水下垂直阵阵元位置测量系统及方法
CN113376568A (zh) * 2021-05-14 2021-09-10 南京航空航天大学 一种基于子空间正交补偿的圆阵doa估计方法
CN113376568B (zh) * 2021-05-14 2023-12-29 南京航空航天大学 一种基于子空间正交补偿的圆阵doa估计方法
CN114114149A (zh) * 2021-11-22 2022-03-01 北京航空航天大学 一种高精度多功能小型水下定位装置
CN114114149B (zh) * 2021-11-22 2024-04-30 北京航空航天大学 一种高精度多功能小型水下定位装置

Also Published As

Publication number Publication date
CN108008348A (zh) 2018-05-08
CN108008348B (zh) 2023-07-18

Similar Documents

Publication Publication Date Title
WO2019095912A1 (zh) 基于可调夹角均匀线阵的水下波达方向估计方法及装置
CN105607033B (zh) 基于正交均匀线阵的水下波达方向估计方法及系统
CN108519576B (zh) 基于夹角可调非均匀线阵的水下波达方向估计方法与装置
CN109633525B (zh) 一种快速的均匀圆阵空间谱测向实现方法
CN107942284B (zh) 基于二维正交非均匀线阵的水下波达方向估计方法与装置
CN108535682B (zh) 一种基于旋转非均匀双l阵的水下二维doa估计方法及装置
JP5480339B2 (ja) 受信専用フェーズドアレイレーダアンテナの較正方法
CN110109053B (zh) 一种未知声速环境下快速doa估计方法
CN109581275B (zh) 基于非圆信号和三维正交阵的二维水下doa估计方法和装置
CN109283511B (zh) 一种宽覆盖多波束接收基阵校准方法
CN106500820B (zh) 一种用于二维波达方向估计的声速测量方法及装置
CN109188019B (zh) 基于多重信号分类算法的三维风速风向测量方法
CN108414967A (zh) 基于夹角可调双l阵的水下二维波达方向估计方法与装置
CN109407048B (zh) 基于非圆信号和夹角可调阵的水下doa估计方法与装置
CN107505548A (zh) 一种基于柔性阵列传感器的局放超声定位方法
CN109521392B (zh) 基于非圆信号和l型线阵的水下一维doa估计方法和装置
CN109581274B (zh) 基于夹角可调三维阵的非圆信号水下doa估计方法和装置
CN110687538A (zh) 一种基于近场聚焦的超波束形成方法
CN113607447A (zh) 一种声学光学联合风机故障定位装置及方法
CN109541573B (zh) 一种弯曲水听器阵列的阵元位置校准方法
CN109884580A (zh) 水下一维doa估计方法和装置
CN208000373U (zh) 基于夹角可调双l阵的水下二维波达方向估计装置
CN112255429B (zh) 一种三维风参数测量方法及系统
CN110824484B (zh) 一种基于恒模算法的阵元位置估计方法
CN207833006U (zh) 一种基于可调夹角均匀线阵的水下波达方向估计装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18877443

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 13/08/2020)

122 Ep: pct application non-entry in european phase

Ref document number: 18877443

Country of ref document: EP

Kind code of ref document: A1