CN113671507A - Waveguide invariant estimation method based on deep sea vertical array - Google Patents
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- 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
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- G—PHYSICS
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- 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
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
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- G01S15/06—Systems determining the position data of a target
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Abstract
The invention discloses a waveguide invariant estimation method based on a deep sea vertical array, and relates to the technical field of underwater acoustic parameter estimation. The technical scheme of the invention comprises the following steps: s1 establishing a waveguide invariant beta and a multi-path time delay parameter bvThe grazing angle of arrival theta of the signal, the time delay of arrival t and the target distance R. S2, the target radiated acoustic signal received by the vertical hydrophone array deployed on the deep sea bottom is utilized to be processed by short-time frequency domain beam forming to obtain a beam delay diagram. S3 clustering the beam delay diagram and extracting the peak point of the beam and the corresponding delay value. S4 curve fits the extracted peaks using least squares to solve for the multipath delay parameters. S5, aiming at different target distance prior information, the waveguide invariant is estimated by combining the actually measured multi-path time delay parameters.
Description
Technical Field
The invention relates to the technical field of underwater acoustic parameter estimation, in particular to a waveguide invariant estimation method based on a deep sea vertical array.
Background
A stable interference structure exists in a low-frequency sound field, and abundant target motion information and marine environment information are contained. Since the introduction of waveguide invariant theory in 1982, Chupurov describes a complex interference structure in a shallow sea sound field by only one scalar, and researchers in later countries are proposed to carry out a great deal of research on waveguide invariance of the sound field from different angles. Brekhovskikh et al briefly expounds the waveguide invariant theory and analyzes the space-frequency interference of the ocean sound field; rouseff et al believe that under the influence of the marine environment, the waveguide invariants should be modeled as a distribution rather than as a constant; at present, the acoustic field waveguide invariant theory is widely applied to passive ranging, underwater acoustic communication, underwater acoustic target identification, ocean parameter monitoring, seabed parameter estimation and the like. The waveguide invariant value changes along with the changes of the waveguide environment and the mode order, so that the method has important application value for accurately extracting the waveguide invariant under different waveguide environments.
The extraction method of the waveguide invariant usually needs to obtain marine environment parameters or target motion information, and application of the algorithm is limited to a great extent. The existing waveguide invariant extracting method includes a method of calculating waveguide invariants by using a frequency shift compensation method, a waveguide invariant extracting method based on Hough transformation, a method of calculating waveguide invariants by using two-dimensional fourier transform ridges of a LOFAR spectrum, a method of extracting waveguide invariants by using beam forming of interference fringes, and the like. The method is aimed at calculating the waveguide invariant of a sound field by a frequency shift compensation method, the method sets the waveguide invariant in a certain range for searching, and finally selects the value of the waveguide invariant as a corresponding value when the spatial correlation coefficient of sound signals received by two hydrophones after frequency shift compensation is maximum, so that the waveguide invariant is estimated. However, both simulation and experiment show that when the frequency is low, the frequency has a certain influence on the value of the waveguide invariant, and the waveguide invariant changes violently along with the frequency. The waveguide invariant extracting method based on Hough transformation utilizes wave beam domain signals for processing, and is strong in noise resistance. The disadvantages are that the method requires that the target must be moving, that the target orientation changes significantly and that the observation time is long enough to be processed in real time. The method for calculating the waveguide invariance by using the two-dimensional Fourier transform ridge of the LOFAR spectrum has small dependence on marine environment parameters, is convenient for extracting the waveguide invariance, and needs to predict the target distance. In addition, the method for extracting the waveguide invariants based on the beam forming of the interference fringes is only suitable for the condition that the included angle between the target azimuth and the array normal transverse direction is less than 30 degrees, and the engineering realization significance is small.
Therefore, a simple method for estimating waveguide invariance under both known and unknown target distances is lacking.
Disclosure of Invention
In view of this, the invention provides a waveguide invariant estimation method based on a deep sea vertical array, which can estimate waveguide invariants under two conditions of known and unknown target distances and is simple and convenient.
In order to achieve the purpose, the technical scheme of the invention comprises the following steps:
s1 establishing a waveguide invariant beta and a multi-path time delay parameter bvThe grazing angle of arrival theta of the signal, the time delay of arrival t and the target distance R.
S2, the target radiated acoustic signal received by the vertical hydrophone array deployed on the deep sea bottom is utilized to be processed by short-time frequency domain beam forming to obtain a beam delay diagram.
S3 clustering the beam delay diagram and extracting the peak point of the beam and the corresponding delay value.
S4 curve fits the extracted peaks using least squares to solve for the multipath delay parameters.
S5, aiming at different target distance prior information, the waveguide invariant is estimated by combining the actually measured multi-path time delay parameters.
Further, the deep sea vertical array-based waveguide invariant estimation method is characterized in that S1 specifically comprises the following steps:
s11: according to definition of waveguide invariants
Deriving therefrom a specific expression of the waveguide invariants, in which the group velocity
Phase velocity
c is the speed of sound; s is used to refer to sin θ; sgIs the group slowness; sPIs the phase slowness.
S12: according to step S11, obtain
S13: the formulas in the step S12 are left and right arranged and integrated to obtain
In which formula b is definedvAs a multi-path delay parameter bvR/(c β); in a beam-time diagram with time t on the abscissa and sin θ on the ordinate, the fitted curve of the direct sound and the multi-path arrival signal satisfies the ellipse equation, and the center of the fitted ellipse is located at (0, t)c) The horizontal major semi-axis of the fitted ellipse is equal to bv。
S14: from the relationship in S13, the relationship among the waveguide invariants, the distance, the sound velocity and the multi-path delay parameter is deduced as
Further, the waveguide invariant estimation method based on the deep sea vertical array is characterized in that S2 comprises the following specific steps:
s21: and selecting a certain channel signal and a time window T, and carrying out Fourier transform on the signal in a limited time period to analyze the frequency component distribution of the target signal.
S22: selecting a signal band fL-fH，fL、fHRespectively the lower limit and the upper limit of the signal frequency band; and performing short-time frequency domain beam forming on all channel signals to obtain a wave arrival pitch angle phi, and taking the remainder to obtain a glancing angle theta of the received sound signals in each time period and a sine value sin theta of the glancing angle theta.
And performing once short-time frequency domain beam forming to obtain a beam-delay diagram and decibel the peak value.
Further, the deep sea vertical array-based waveguide invariant estimation method is characterized in that S3 comprises the following steps:
s31: after the beam delay pattern is obtained through the step S2, a peak point where the peak value is higher than the set threshold is found.
S32: and classifying a plurality of peak points with close arrival time, namely, when the arrival time interval of two peak points is less than a set time threshold, regarding the two peak points as a set.
S3: selecting the point of the peak value maximum value from a plurality of clustered peak value sets
{smax(t1),smax(t2),...,smax(tN) }; wherein s ismax(t1),smax(t2),...,smax(tN) 1 st to Nth peak maximum points, t1～tNRespectively time delay values of the 1 st peak value to the Nth peak value maximum point.
Further, the waveguide invariant estimation method based on the deep sea vertical array is characterized in that the S4 comprises the following sub-steps:
s41: an ellipse fitting is performed on the peak maximum point in S33 using a least squares estimation.
S42: and calculating the value of the horizontal major semi-axis of the ellipse after obtaining the fitting ellipse equation.
S43: the value of the ellipse horizontal major semiaxis obtained by S42 is the multi-path time delay parameter bv。
Further, the waveguide invariant estimation method based on the deep sea vertical array is characterized in that the S5 comprises the following sub-steps:
for the case that the target distance is known, combining the relation of each parameter in the step S14, and combining R and bvAnd c, substituting the three parameters into a formula to obtain the waveguide invariant at the distance.
Aiming at the condition that the target distance is unknown, combining sound velocity distribution measured by a test, and simulating a curve that the pitch angle changes along with the distance by using BELLHOP; estimating a target pitch angle by combining the step S2, estimating a target distance by using a pitch angle matching method, and substituting the target distance into the formula of the step S14 to estimate the waveguide invariant.
Has the advantages that:
1. the method considers the calculation of the waveguide invariant under the known and unknown target distances, utilizes the geometric relationship between the waveguide invariant and the multi-path arrival time delay under different distances, estimates the waveguide invariant under the known and unknown target distances, and is simple and convenient.
2. The waveguide invariant estimation method based on the deep sea vertical array provided by the invention fully utilizes array gain, has small dependence on marine environment and low calculation complexity, can save a large amount of algorithm calculation time, and is more suitable for engineering practical application.
Drawings
FIG. 1 is a flow chart of a waveguide invariant estimation method based on a deep sea vertical array;
FIG. 2 is a diagram of experimental equipment deployment;
FIG. 3 is a graph of least squares elliptic curve fit results;
FIG. 4 is a plot of experimental sea velocity profiles;
FIG. 5 is a graph of pitch angle of arrival of an acoustic signal as a function of distance;
FIG. 6 is a graph of waveguide invariant estimation results;
FIG. 7 is a graph of waveguide invariant estimation versus error.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The invention provides a flow chart of a waveguide invariant estimation method based on a deep sea vertical array, which is shown in figure 1, and the waveguide invariant under different distances is estimated on the basis of the flow chart. In this example, consider a linear array of vertical hydrophones deployed near the seafloor, with a number of array elements of 15, an array element spacing of 7.5m, a vertical array equivalent depth of 4105.5m, and a sea depth of 4262 m. The experimental ship drags the air gun sound source to do uniform linear motion from near to far, and the motion speed is about 4 knots. The air gun emits signals every 90s, the equivalent depth of the air gun is about 10m, and the sound source distance is about 5km-20 km. The experimental setup deployment is shown in figure 2.
Taking the target distance of 10.006km as an example, the waveguide invariant estimation step of the deep sea vertical array is as follows:
s1, according to the relation between the waveguide quantity and the multi-path time delay parameter, establishing the waveguide value beta and the multi-path time delay parameter bvThe grazing angle theta of signal arrival, the arrival time delay t and the distance R; the relationship between the parameters is
In the above formula, b is definedvR/(c β) is a multipath delay parameter. In a beam-time diagram with time t on the abscissa and sin θ on the ordinate, the curve fitted by the direct sound and the multipath reflected signal satisfies the ellipse equation, and the ellipse center is located at (0, t)c)，bvIs the horizontal major semi-axis of the ellipse. Deducing the relation among the waveguide invariants, the distance, the sound velocity and the multi-path time delay parameters as
S2, the target radiated sound signals received by the vertical hydrophone array deployed near the deep sea bottom are processed by frequency domain beam forming to obtain a beam-time delay diagram.
The specific steps of obtaining the beam-delay diagram in step S2 are as follows:
s21 selects a channel signal and a time window T, and performs fourier transform on the signal in a limited time period to analyze the frequency component distribution of the target signal, in this example, 5 channels are selected to analyze the frequency component of the signal, and the time window T is 30S.
S22 selecting signal frequency band fL-fHPerforming short-time frequency domain beam forming on the 15-channel signals to obtain a wave arrival pitch angle phi, and taking the remainder to obtain a grazing angle theta of the received sound signals in each time period and a sine value sin theta of the grazing angle theta; in this example, # ═ 21 °, fL＝20Hz，fHAnd (5) performing short-time frequency domain beam forming every 0.2 seconds (500 Hz), obtaining a beam-delay diagram and decibelizing the peak value.
S3 clustering the beam delay diagram and extracting a beam peak point and a corresponding delay value; the method comprises the following specific steps:
s31 finding out the peak point whose peak value is higher than the set threshold-10 dB;
s32 clusters a plurality of peak points that arrive close in time. When the time interval between two peak points is less than 2ms, the peak points are regarded as a set;
s33 selecting maximum value S from each clustered peak point setmax(t1),smax(t2),...,smax(tN)}。
S4, performing curve fitting by using a least square method so as to solve the multi-path time delay parameter; the method comprises the following specific steps:
s41 assumes the elliptical equation to be Ax2+2Bxy+Cy2+2(Dx + Ey) + F ═ 0, where
F＝1,
A+C＝1,
A2+B2+C2+D2+E2+F2＝1,
A2+2B2+C2＝1,
AC-B2＝1.
Namely, the ellipse equation is normalized;
s42 defines vector xi ═ x2,2xy,y2,2x,2y,1)T，θ＝(A,B,C,D,E,F)TThen, the elliptic equation can be expressed as (ξ, θ) ═ 0, where (α, β) represents the inner product of α, β.
S43 calculates coefficients a, B, C, D, E, F using a least square method to obtain an elliptic equation, and then fits the peak points obtained in step S33 with the elliptic equation. When the least squares estimator makes
When the minimum value is small, the corresponding elliptic equation is the elliptic equation obtained by fitting, and the horizontal semi-major axis of the equation is the multi-path time delay parameter bv. The ellipse fitting is performed on the peak points in this example, and the result is shown in FIG. 3.
S5, aiming at different target distance prior information, estimating a waveguide invariant by combining the actually measured multi-path delay parameter;
the method comprises the following specific steps:
s51 combining the relation of each parameter in the S14 step to R, b for the condition that the target distance is knownvC, substituting the three parameters into a formula to obtain a waveguide invariant under the distance; in this example, R is 10.006km, bv5.8693, c 1530m/s, and 1.1143 is calculated as the waveguide invariant β.
S52 simulates the curve of pitch angle of arrival with distance (fig. 5) using BELLHOP in conjunction with experimentally measured sound velocity distribution (fig. 4) for unknown target distance. Estimating the target pitch angle in combination with the step of S2
And matching the pitch angle estimation target distance R to be 9.85km, and substituting the matching pitch angle estimation target distance R into the S1 step formula to estimate the waveguide invariant beta to be 1.0969.
The distance estimation is carried out by using the air gun sound signals with the target distance range of 5km-20km, the waveguide invariants with different distances estimated by the method are compared with simulated values, and the result and the error are shown in the figures 6 and 7. Aiming at the known target distance, the waveguide invariant estimation value is basically consistent with a theoretical calculation value, the relative error is within 10 percent, and the estimation precision is high; aiming at the situation that the target distance is unknown, the estimation effect is good in the range of less than 17km, and the relative error is within 15%. At distances greater than 17km, the waveguide invariance estimation results are poor. Analysis is performed by combining the graph 5, and it can be known that when the target distance is estimated by using the matching pitch angle method under the condition of unknown target distance, the pitch angle of the vertical array received signal is obviously changed along with the distance under the condition of medium and short distance, and the estimated distance is accurate, so that the calculated waveguide invariant precision is high. For a target at a longer distance (more than 17km), the pitch angle changes slowly with the distance, and the azimuth estimation precision greatly influences the solution of the distance, so that the solution of the subsequent waveguide invariant is also influenced greatly.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A waveguide invariant estimation method based on a deep sea vertical array is characterized by comprising the following steps:
s1 establishing a waveguide invariant beta and a multi-path time delay parameter bvThe grazing angle theta of signal arrival, the arrival time delay t and the target distance R;
s2, carrying out short-time frequency domain beam forming processing on a target radiated acoustic signal received by a vertical hydrophone array deployed on the deep sea bottom to obtain a beam time delay diagram;
s3 clustering the beam delay diagram and extracting a beam peak point and a corresponding delay value;
s4, performing curve fitting by using a least square method aiming at the peak of the extracted wave beam so as to solve a multi-path time delay parameter;
s5, aiming at different target distance prior information, the waveguide invariant is estimated by combining the actually measured multi-path time delay parameters.
2. The deep sea vertical array-based waveguide invariant estimation method of claim 1, wherein S1 specifically comprises the following steps:
s11: according to definition of waveguide invariants
Deriving therefrom a specific expression of the waveguide invariants, in which the group velocity
Phase velocity
c is the speed of sound; s is used to refer to sin θ; sgIs the group slowness; sPIs the phase slowness;
s12: according to step S11, obtain
S13: the formulas in the step S12 are left and right arranged and integrated to obtain
In which formula b is definedvAs a multi-path delay parameter bvR/(c β); in a beam-time diagram with time t on the abscissa and sin θ on the ordinate, the fitted curve of the direct sound and the multi-path arrival signal satisfies the ellipse equation, and the center of the fitted ellipse is located at (0, t)c) The horizontal major semi-axis of the fitted ellipse is equal to bv；
S14: from the relationship in S13, the relationship among the waveguide invariants, the distance, the sound velocity and the multi-path delay parameter is deduced as
3. The deep sea vertical array-based waveguide invariant estimation method of claim 2, wherein S2 comprises the following specific steps:
s21: selecting a certain channel signal and a time window T, and carrying out Fourier transform on the signal in a limited time period to analyze the frequency component distribution of a target signal;
s22: selecting a signal band fL-fH，fL、fHRespectively the lower limit and the upper limit of the signal frequency band; performing short-time frequency domain beam forming on all channel signals to obtain a wave arrival pitch angle phi, and taking the remainder to obtain a glancing angle theta of the received sound signals in each time period and a sine value sin theta of the glancing angle theta;
and performing once short-time frequency domain beam forming to obtain a beam-delay diagram and decibel the peak value.
4. The deep sea vertical array based waveguide invariance estimation method according to claim 3, wherein S3 comprises the steps of:
s31: after the beam delay diagram is obtained in the step S2, finding a peak point of which the peak value is higher than a set threshold;
s32: classifying a plurality of peak points with adjacent arrival time, namely regarding two peak points as a set when the arrival time interval of the two peak points is less than a set time threshold;
s3: selecting the point of the peak value maximum value from a plurality of clustered peak value sets
{smax(t1),smax(t2),...,smax(tN) }; wherein s ismax(t1),smax(t2),...,smax(tN) 1 st to Nth peak maximum points, t1～tNRespectively time delay values of the 1 st peak value to the Nth peak value maximum point.
5. The deep sea vertical array based waveguide invariance estimation method according to claim 4, wherein S4 comprises the following sub-steps:
s41: fitting an ellipse to the peak maximum point in S33 using least squares estimation;
s42: calculating the value of the horizontal major semi-axis of the ellipse after obtaining a fitting ellipse equation;
s43: the value of the ellipse horizontal major semiaxis obtained by S42 is the multi-path time delay parameter bv。
6. The deep sea vertical array based waveguide invariance estimation method according to claim 1, wherein S5 comprises the sub-steps of:
for the case that the target distance is known, combining the relation of each parameter in the step S14, and combining R and bvC, substituting the three parameters into a formula to obtain a waveguide invariant under the distance;
aiming at the condition that the target distance is unknown, combining sound velocity distribution measured by a test, and simulating a curve that the pitch angle changes along with the distance by using BELLHOP; estimating a target pitch angle by combining the step S2, estimating a target distance by using a pitch angle matching method, and substituting the target distance into the formula of the step S14 to estimate the waveguide invariant.
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| CN115982571A (en) * | 2023-01-12 | 2023-04-18 | 中国人民解放军军事科学院系统工程研究院 | Geometric representation method and device for space terahertz communication signals |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060133211A1 (en) * | 2004-12-17 | 2006-06-22 | Yang Tsih C | Method and apparatus for acoustic source tracking using a horizontal line array |
| CN103487796A (en) * | 2013-09-23 | 2014-01-01 | 河海大学常州校区 | Method for using underwater acoustic channel statistics invariant features to achieve passive ranging |
| CN104714235A (en) * | 2013-12-16 | 2015-06-17 | 中国科学院声学研究所 | Ranging method and system for double low-frequency vector hydrophone arrays |
| CN106646373A (en) * | 2016-12-16 | 2017-05-10 | 西北工业大学 | Short-distance sound source combined positioning method based on shallow-sea multipath arrival angle and arrival time delay |
| US20180128909A1 (en) * | 2016-11-10 | 2018-05-10 | Northwestern Polytechnical University | Method for obtaining horizontal longitudinal correlation of deep-sea great-depth sound field |
| CN109506763A (en) * | 2018-11-30 | 2019-03-22 | 中国人民解放军军事科学院国防科技创新研究院 | A kind of vector hydrophone thinned arrays method based on learning aid optimization |
| CN112305502A (en) * | 2020-10-26 | 2021-02-02 | 西北工业大学 | Water surface and underwater sound source binary discrimination method based on array invariants |
| CN112987004A (en) * | 2021-02-05 | 2021-06-18 | 中国人民解放军国防科技大学 | Water surface and underwater target classification method based on horizontal array in shallow sea environment |
| CN113030979A (en) * | 2021-05-26 | 2021-06-25 | 北京星天科技有限公司 | Method and device for detecting position depth of target object |
-
2021
- 2021-07-14 CN CN202110797097.3A patent/CN113671507B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060133211A1 (en) * | 2004-12-17 | 2006-06-22 | Yang Tsih C | Method and apparatus for acoustic source tracking using a horizontal line array |
| CN103487796A (en) * | 2013-09-23 | 2014-01-01 | 河海大学常州校区 | Method for using underwater acoustic channel statistics invariant features to achieve passive ranging |
| CN104714235A (en) * | 2013-12-16 | 2015-06-17 | 中国科学院声学研究所 | Ranging method and system for double low-frequency vector hydrophone arrays |
| US20180128909A1 (en) * | 2016-11-10 | 2018-05-10 | Northwestern Polytechnical University | Method for obtaining horizontal longitudinal correlation of deep-sea great-depth sound field |
| CN106646373A (en) * | 2016-12-16 | 2017-05-10 | 西北工业大学 | Short-distance sound source combined positioning method based on shallow-sea multipath arrival angle and arrival time delay |
| CN109506763A (en) * | 2018-11-30 | 2019-03-22 | 中国人民解放军军事科学院国防科技创新研究院 | A kind of vector hydrophone thinned arrays method based on learning aid optimization |
| CN112305502A (en) * | 2020-10-26 | 2021-02-02 | 西北工业大学 | Water surface and underwater sound source binary discrimination method based on array invariants |
| CN112987004A (en) * | 2021-02-05 | 2021-06-18 | 中国人民解放军国防科技大学 | Water surface and underwater target classification method based on horizontal array in shallow sea environment |
| CN113030979A (en) * | 2021-05-26 | 2021-06-25 | 北京星天科技有限公司 | Method and device for detecting position depth of target object |
Non-Patent Citations (16)
| Title |
|---|
| C. GERVAISE: "Passive geoacoustic inversion with a single hydrophone using broadband ship noise", 《THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA》 * |
| CHUN-XIAO LI: "An Iterative Deconvolution-Time Reversal Method with Noise Reduction, a High Resolution and Sidelobe Suppression for Active Sonar in Shallow Water Environments", 《SENSORS》 * |
| TIAN, LING-AI: "Extraction of the waveguide invariant from a shallow-water acoustical experiment", 《AIP CONFERENCE PROCEEDINGS [AIP SHALLOW-WATER ACOUSTICS: PROCEEDINGS OF THE SECOND INTERNATIONAL SHALLOW-WATER ACOUSTICS CONFERENCE (SWAC’09) - SHANGHAI 》 * |
| TONGSHENG SHEN: "Infrared image segmentation method based on spatial coherence histogram and maximum entropy", 《PROC. SPIE 9275, INFRARED, MILLIMETER-WAVE, AND TERAHERTZ TECHNOLOGIES III》 * |
| 余;惠俊英;殷敬伟;惠娟;王自娟;: "基于波导不变量的目标运动参数估计及被动测距", 声学学报 * |
| 刘爱国;察豪;刘峰;: "基于雷达海杂波的大气折射率剖面估计技术", 电波科学学报 * |
| 唐凯;周德富;韩庆邦;李建;范洪辉;殷澄;朱昌平;: "基于波导不变量的双阵元被动探测方法研究", 声学技术 * |
| 孟路稳;罗夏云;程广利;尚建华;张明敏;: "基于单水听器的移动声源运动参数估计", 船舶力学 * |
| 安良;王志强;陆佶人;: "利用LOFAR谱图的二维傅里叶变换脊计算波导不变量", 电子与信息学报 * |
| 李茂震: "浅海声场波导不变量提取技术", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 海伟: "浅海波导不变量计算方法研究", 《海洋技术学报》 * |
| 海伟;石敏;储泽国;: "浅海波导不变量计算方法研究", 海洋技术学报 * |
| 王朋;郑胜家;黄勇;刘纪元;: "浅海运动目标波束域波导不变量测距方法研究", 声学学报 * |
| 王炳辉;余;: "波导不变量和航向角联合估计方法研究", 声学技术 * |
| 高伟: "浅海波导中简正波相干分量的奇异值分解提取方法", 《声学学报》 * |
| 高伟;王宁;陈川;: "利用船舶噪声的自相关与倒谱联合估计多径时延", 声学学报 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115982571A (en) * | 2023-01-12 | 2023-04-18 | 中国人民解放军军事科学院系统工程研究院 | Geometric representation method and device for space terahertz communication signals |
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