CN109270516B - Beam forming method suitable for unmanned mobile platform to detect naval vessel line spectrum - Google Patents

Beam forming method suitable for unmanned mobile platform to detect naval vessel line spectrum Download PDF

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CN109270516B
CN109270516B CN201811017221.4A CN201811017221A CN109270516B CN 109270516 B CN109270516 B CN 109270516B CN 201811017221 A CN201811017221 A CN 201811017221A CN 109270516 B CN109270516 B CN 109270516B
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CN109270516A (en
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王逸林
邹男
马世龙
梁国龙
曲坦
王晋晋
张光普
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Harbin Engineering University
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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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
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Abstract

A beam forming method suitable for detecting a naval vessel line spectrum by an unmanned mobile platform belongs to the field of signal processing. The invention mainly comprises the following steps: setting basic parameters; filtering array element receiving signals by a multi-path tap delay line to obtain the output of a time domain broadband beam former; carrying out coherent time delay removal and multi-path tap delay line filtering processing on the array element receiving signal to obtain a non-external target line spectrum reference signal; and adaptively adjusting the weight vector of the time domain broadband beam former, namely updating the weight vector of the multi-path tap delay line by taking the minimum mean square error of the target line spectrum reference signal and the output of the time domain broadband beam former as a criterion. The method can adaptively point the main beam direction to the line spectrum target direction, and can realize the detection of the ship target by performing the line spectrum autonomous detection on the output of the self-guiding beam, so that a plurality of preformed beams are not needed, and the complexity of detecting the ship line spectrum based on the unmanned mobile platform is simplified.

Description

Beam forming method suitable for unmanned mobile platform to detect naval vessel line spectrum
Technical Field
The invention belongs to the field of signal processing, and particularly relates to a beam forming method suitable for detecting a naval vessel line spectrum by an unmanned mobile platform.
Background
The method takes passive target detection by an unmanned mobile platform by using a sound ray spectrum signal in underwater target radiation noise as a research background. At present, a convenient and effective method is to record and analyze a history map by using a Multi-Beam Low Frequency line spectrum, that is, a Multiple Beam Low Frequency Analysis Recording spectrum, which is abbreviated as a Multi-Beam Low Frequency spectrum, and the method adopts a pre-Multi-Beam forming mode to obtain time domain signal output of each direction, and analyzes and extracts line spectrum signals from time domain output results of each direction. The pre-forming multi-beam method is widely applied to a manned sonar passive detection system, and a sonar operator assists in judging to realize passive detection of a line spectrum target. The method applied to the unmanned mobile platform has the problems of difficult orientation-frequency-time multi-dimensional information fusion and the like, and particularly when the target orientation is changed rapidly, the target line spectrum is alternately displayed among a plurality of beam outputs, so that the autonomous analysis and extraction of the target line spectrum are not facilitated.
Disclosure of Invention
The invention aims to provide a beam forming method suitable for detecting a naval vessel line spectrum by an unmanned mobile platform, and solves the problems of difficult multi-dimensional information fusion and the like in the application of a multi-beam low-frequency line spectrum recording and analyzing process chart line spectrum detection method in an unmanned sonar system.
The purpose of the invention is realized as follows:
a beam forming method suitable for detecting a naval vessel line spectrum by an unmanned mobile platform comprises the following steps:
(1) setting basic parameters, wherein the basic parameters comprise: sampling rate, the number of taps of a tapped delay line, the number of array elements of a uniform linear array, self-adaptive step length, coherent time resolution and an interested subspace;
(2) calculating the output of the time domain broadband beam former, namely filtering the array element receiving signals by a multi-path tap delay line to obtain the output of the time domain broadband beam former;
(3) acquiring a target line spectrum reference signal, namely performing coherent time delay removal and multi-path tap delay line filtering processing on an array element receiving signal to obtain a non-external target line spectrum reference signal;
(4) adaptively adjusting the weight vector of the time domain broadband beam former, namely updating the weight vector of the multi-path tap delay line in the step (2) by taking the minimum mean square error of the target line spectrum reference signal in the step (3) and the output of the time domain broadband beam former in the step (2) as a criterion;
(5) and (3) starting to execute from the step (2) again.
The specific process of calculating the output of the time domain broadband beam former in the step (2) is as follows:
let the array element receive signal be X (n) ═ x0(n),…,xM-1(n),x0(n-1),…,xM-1(n-1),…,xM-1(n-L+1)]TWherein x ism(n) is the M number array element receiving signal at the time of n, M is the number of array elements of the uniform linear array, L is the number of taps of the tapped delay line, T is the mathematical symbol vector transposition, the array element receiving signal X (n) is filtered by the multi-path tapped delay line to obtain the output of a time domain broadband beam former, and the mathematical expression of the process is as follows:
y(n)＝WH(n)X(n)
wherein W (n) ═ w0,0(n),…,w0,M-1(n),w1,0(n),…,w1,M-1(n),…,wL-1,M-1(n)]TIs the weight vector, w, of the multi-tap delay line in step (2)l,m(n) is the weight of the first tap of the tap delay line after the m-th array element at the n moment, and y (n) is the output of the time domain broadband beam former.
The specific process of acquiring the target line spectrum reference signal in the step (3) is as follows:
obtaining a target line spectrum reference signal by performing time delay decorrelation and multi-path tap delay line filtering on an array element receiving signal X (n), wherein the mathematical expression of the process is as follows:
Figure BDA0001786079580000021
wherein Wq＝[wq_0,0,…,wq_0,M-1,wq_1,0,…,wq_1,M-1,…,wq_L-1,M-1]TIs the step of(3) Weight vector, w, of said multi-tap delay lineq_l,mThe weight of the first tap of the m-th tap delay line, delta is the decorrelation time, d (n) is the target line spectrum reference signal, WqFor a fixed weight vector, the convex optimization expression is obtained by solving the following formula with a convex optimization tool:
Figure BDA0001786079580000022
Figure BDA0001786079580000023
Figure BDA0001786079580000024
Figure BDA0001786079580000025
wherein minmax | represents minimizing the maximum absolute value of the expression in | represents taking absolute value, | | | | | represents taking 2 norm of vector, s.t. the constraint condition to be satisfied is as follows,
Figure BDA0001786079580000026
denotes an arbitrary value, δΘRepresenting a constant beam width constraint coefficient, f0Representing a reference frequency point in a constant beam width constraint,
Figure BDA0001786079580000027
is the stopband constraint coefficient, δnormFor the robustness constraint coefficient, θ is the subspace of interest, θΘFor each azimuthal angle within the space theta,
Figure BDA0001786079580000028
in order not to be a subspace of interest,
Figure BDA0001786079580000029
is emptyWorkshop
Figure BDA00017860795800000210
Inner azimuth angle, omega, system operating bandwidth, fΩFor each frequency point within the bandwidth Ω, a (f, θ) is a LM × 1-dimensional steering vector written as:
Figure BDA0001786079580000031
Figure BDA0001786079580000032
al,m＝cos(2πfl/fs+2πfsin(θ)dm/C)，l＝0,1,...,L-1,m＝0,1,...,M-1
wherein C is the sound velocity in water, d is the array element spacing of the uniform linear array, fsFor the sampling rate, f and θ are parametric variables, at fΩ、f0And
Figure BDA0001786079580000033
θΘselecting.
The specific process of the adaptive adjustment of the weight vector of the time domain broadband beam former in the step (4) is as follows:
the minimum mean square error between the target line spectrum reference signal d (n) in the step (3) and the output y (n) of the time domain broadband beam former in the step (2) is:
ξ(W(n))＝E{|d(n)-y(n)|2}＝E{|d(n)-WT(n)X(n)|2}
wherein E { } represents the signal expectation, ξ (W (n))) represents the minimum mean square error of d (n) and y (n), and the minimization ξ (W (n)) is taken as a criterion to obtain an adaptive adjustment formula of a weight vector W (n):
W(n+1)＝W(n)+με(n)X(n)
where ∈ (n) ═ d (n) — (n) y (n) denotes a residual of the adaptation process, μ is an adaptation step size, and the weight vector W (n +1) at the next time is updated by an arithmetic expression.
The invention has the beneficial effects that:
under the condition that prior information such as a line spectrum target position, a line spectrum frequency, a target motion state and the like is lost, the beam forming method provided by the invention can adaptively point the main beam direction to the line spectrum target position, and the detection of the ship target can be realized by performing line spectrum autonomous detection on the output of the self-guided beam, so that a plurality of beams do not need to be preformed, and the complexity of detecting the ship line spectrum based on an unmanned mobile platform is simplified.
Drawings
Fig. 1 is a schematic block diagram of the proposed beamforming method;
FIG. 2 is a diagram of a multi-beam low-frequency line spectrum recording and analyzing process;
FIG. 3 is a plot of the low frequency line spectrum recorded and analyzed for the 100 ° azimuth beam output of FIG. 2;
fig. 4 is the output of the proposed beamforming method.
Detailed Description
The present invention is described in further detail below with reference to the accompanying drawings.
A beam forming method suitable for detecting a naval vessel line spectrum by an unmanned mobile platform comprises the following steps:
(1) setting basic parameters, wherein the basic parameters comprise: sampling rate, the number of taps of a tapped delay line, the number of array elements of a uniform linear array, self-adaptive step length, coherent time resolution and an interested subspace;
(2) calculating the output of the time domain broadband beam former, namely filtering array element receiving signals by a multi-path tap delay line to obtain the output of the time domain broadband beam former;
(3) acquiring a target line spectrum reference signal, namely performing coherent time delay removal and multi-path tap delay line filtering processing on an array element receiving signal to obtain a non-external target line spectrum reference signal;
(4) adaptively adjusting the weight vector of the time domain broadband beam former, namely updating the weight vector of the multi-path tap delay line in the step (2) by taking the minimum mean square error of the target line spectrum reference signal in the step (3) and the output of the time domain broadband beam former in the step (2) as a criterion;
(5) and (5) starting to execute from the step (2) again.
The specific process of calculating the output of the time domain broadband beam former in the step (2) is as follows:
let the array element receive signal be X (n) ═ x0(n),…,xM-1(n),x0(n-1),…,xM-1(n-1),…,xM-1(n-L+1)]TWherein x ism(n) is the M number array element receiving signal at the time of n, M is the number of array elements of the uniform linear array, L is the number of taps of the tapped delay line, T is the mathematical symbol vector transposition, the array element receiving signal X (n) is filtered by the multi-path tapped delay line to obtain the output of a time domain broadband beam former, and the mathematical expression of the process is as follows:
y(n)＝WH(n)X(n)
wherein W (n) ═ w0,0(n),…,w0,M-1(n),w1,0(n),…,w1,M-1(n),…,wL-1,M-1(n)]TIs the weight vector, w, of the multi-tap delay line in step (2)l,m(n) is the weight of the first tap of the tap delay line after the m-th array element at the n moment, and y (n) is the output of the time domain broadband beam former. The structure of a multi-tap Delay Line, called Tapped Delay Line, TDL for short, is shown as TDLs part in fig. 1.
The specific process of acquiring the target line spectrum reference signal in the step (3) is as follows:
as shown in fig. 1, after time Δ delay decoherence, array element receiving signals x (n) are subjected to multi-tap delay lines TDLs to filter out line spectrum interference in a non-interested region, and a target line spectrum reference signal is obtained, and the mathematical expression of the process is as follows:
Figure BDA0001786079580000041
wherein Wq＝[wq_0,0,…,wq_0,M-1,wq_1,0,…,wq_1,M-1,…,wq_L-1,M-1]TIs the weight vector, w, of the multi-tap delay line in step (3)q_l,mThe weight of the first tap of the m-th tap delay line is Δ is the decorrelation time, and d (n) is the target line spectrum reference signal. It is composed ofMiddle WqThe weight vector is a fixed weight vector and is obtained by solving the following convex optimization expression by a convex optimization tool;
Figure BDA0001786079580000051
Figure BDA0001786079580000052
Figure BDA0001786079580000053
Figure BDA0001786079580000054
wherein minmax | represents minimizing the maximum absolute value of the expression in | represents taking absolute value, | | | | | represents taking 2 norm of vector, s.t. the constraint condition to be satisfied is as follows,
Figure BDA0001786079580000055
any value is indicated. DeltaΘRepresenting a constant beam width constraint coefficient, f0Representing a reference frequency point in a constant beam width constraint.
Figure BDA0001786079580000056
To stop band constraint coefficient, δnormAre robustness constraint coefficients. Theta is the subspace of interest, thetaΘIs the azimuthal angle within the space theta.
Figure BDA0001786079580000057
In the form of a sub-space of no interest,
Figure BDA00017860795800000513
is a space
Figure BDA0001786079580000058
Each azimuthal angle in. Omega is the systemOperating bandwidth, fΩAt each frequency point within the bandwidth omega. a (f, θ) is a LM × 1-dimensional steering vector written as:
Figure BDA0001786079580000059
Figure BDA00017860795800000510
al,m＝cos(2πfl/fs+2πfsin(θ)dm/C)，l＝0,1,...,L-1,m＝0,1,...,M-1
wherein C is the sound velocity in water, d is the array element spacing of the uniform linear array, fsIs the sampling rate. f and theta are parameter variables, at fΩ，f0，
Figure BDA00017860795800000511
θΘSelecting. The above-mentioned fixed weight vector WqThe design ensures that the signal within the space of interest Θ passes approximately undistorted, rather than the subspace of interest
Figure BDA00017860795800000512
The signal in is suppressed.
The specific process of the adaptive adjustment of the weight vector of the time domain broadband beam former in the step (4) is as follows:
the minimum mean square error between the target line spectrum reference signal d (n) in the step (3) and the output y (n) of the time domain broadband beam former in the step (2) is:
ξ(W(n))＝E{|d(n)-y(n)|2}＝E{|d(n)-WT(n)X(n)|2}
where E { } denotes the signal expectation. ξ (W (n)) represents the minimum mean square error of d (n) and y (n). Obtaining the adaptive adjustment formula of the weight vector W (n) by taking the minimization xi (W (n)) as a criterion
W(n+1)＝W(n)+με(n)X(n)
Where ∈ (n) ═ d (n) -y (n) denotes the residual of the adaptation process, and μ is the adaptation step size. The weight vector W (n +1) at the next time instant is updated by an arithmetic expression. The above-mentioned weight vector adaptive adjustment process is shown in fig. 1.
The first embodiment is as follows:
(1) setting basic parameters, wherein the basic parameters comprise: sampling rate, the number of taps of a tapped delay line, the number of array elements of a uniform linear array, self-adaptive step length, coherent time resolution and an interested subspace;
sampling rate: f. ofs2.5 kHz; number of taps of tapped delay line: l ═ 30; the number of array elements of the uniform linear array is as follows: m ═ 20; self-adaptive step length: μ ═ 0.01; releasing coherence time: Δ ═ 0.1 s; subspace of interest: and theta is 50-130 degrees.
(2) Calculating the output of the time domain broadband beam former, namely filtering array element receiving signals by a multi-path tap delay line to obtain the output of the time domain broadband beam former;
(3) acquiring a target line spectrum reference signal, namely performing coherent time delay removal and multi-path tap delay line filtering processing on an array element receiving signal to obtain a non-external target line spectrum reference signal;
(4) self-adaptive adjustment of the weight vector of the time domain broadband beam former is carried out, namely the weight vector of the multi-path tap delay line in the step (2) is updated by taking the minimum mean square error output by the target line spectrum reference signal in the step (3) and the time domain broadband beam former in the step (2) as a criterion;
(5) and (3) starting to execute from the step (2) again.
FIGS. 2-4 show that the line spectrum target contains 495Hz, 475Hz and 415Hz line spectra, and the signal-to-noise ratio of each line spectrum is-20 dB. The line spectral object changes rapidly from a 70 ° orientation to a 120 ° orientation within the subspace of interest Θ. The line spectrum interference exists in the 160-degree position, the line spectrum frequency is 360Hz and 440Hz, and the multi-beam low-frequency line spectrum recording and analyzing process chart and the output result of the beam forming method provided by the invention under the condition that the interference-to-noise ratio is 5 dB. Fig. 2 is a multi-beam low-frequency line spectrum recording and analyzing process diagram, and due to the rapid change of the target azimuth, the target line spectrum appears in sequence in each beam output for a short time, so that the line spectrum autonomous detection is inconvenient to directly carry out. Fig. 3 is a low-frequency line spectrum recording and analyzing history chart of the 100 ° azimuth beam output in fig. 2, from which a target line spectrum appearing in a short time can be clearly observed. Fig. 4 is the output of the proposed beamforming method, from which it can be seen that the target line spectrum is continuously displayed within the whole observation time, making further autonomous detection of the line spectrum more efficient and convenient. Therefore, the complexity of detecting the ship line spectrum based on the unmanned mobile platform is reduced.

Claims (4)

1. A beam forming method suitable for detecting a naval vessel line spectrum by an unmanned mobile platform is characterized by comprising the following steps:
(1) setting basic parameters, wherein the basic parameters comprise: sampling rate, the number of taps of a tapped delay line, the number of array elements of a uniform linear array, self-adaptive step length, coherent time resolution and an interested subspace;
(2) calculating the output of the time domain broadband beam former, namely filtering array element receiving signals by a multi-path tap delay line to obtain the output of the time domain broadband beam former;
(3) acquiring a target line spectrum reference signal, namely performing coherent time delay removal and multi-path tap delay line filtering processing on an array element receiving signal to obtain a non-external target line spectrum reference signal;
(4) adaptively adjusting the weight vector of the time domain broadband beam former, namely updating the weight vector of the multi-path tap delay line in the step (2) by taking the minimum mean square error of the target line spectrum reference signal in the step (3) and the output of the time domain broadband beam former in the step (2) as a criterion;
(5) and (5) starting to execute from the step (2) again.
2. The beamforming method suitable for the unmanned mobile platform to detect the naval vessel line spectrum according to claim 1, wherein the specific process of calculating the output of the time domain broadband beamformer in the step (2) is as follows:
let the array element receive signal be X (n) ═ x0(n),…,xM-1(n),x0(n-1),…,xM-1(n-1),…,xM-1(n-L+1)]TWherein x ism(n) M is the M-th array element receiving signal at n time, M is the array element of uniform linear arrayThe number, L is the number of taps of the tapped delay line, T is the mathematical symbol vector transposition, the array element receiving signal X (n) is filtered by the multi-tap delay line to obtain the output of the time domain broadband beam former, and the mathematical expression of the process is as follows:
y(n)＝WH(n)X(n)
wherein W (n) ═ w0,0(n),…,w0,M-1(n),w1,0(n),…,w1,M-1(n),…,wL-1,M-1(n)]TIs the weight vector, w, of the multi-tap delay line in step (2)l,m(n) is the weight of the first tap of the tap delay line after the m-th array element at the n moment, and y (n) is the output of the time domain broadband beam former.
3. The beam forming method suitable for the unmanned mobile platform to detect the naval vessel line spectrum according to claim 2, wherein the specific process of acquiring the target line spectrum reference signal in the step (3) is as follows:
obtaining a target line spectrum reference signal by performing time delay decorrelation and multi-path tap delay line filtering on an array element receiving signal X (n), wherein the mathematical expression of the process is as follows:
Figure FDA0003503635130000011
wherein Wq＝[wq_0,0,…,wq_0,M-1,wq_1,0,…,wq_1,M-1,…,wq_L-1,M-1]TIs the weight vector, w, of the multi-tap delay line in step (3)q_l,mThe weight of the first tap of the m-th tap delay line, delta is the decorrelation time, d (n) is the target line spectrum reference signal, WqFor a fixed weight vector, the convex optimization expression is obtained by solving the following formula with a convex optimization tool:
Figure FDA0003503635130000021
Figure FDA0003503635130000022
Figure FDA0003503635130000023
Figure FDA0003503635130000024
wherein minmax | represents minimizing the maximum absolute value of the expression in | represents taking absolute value, | | | | | represents taking 2 norm of vector, s.t. the constraint condition to be satisfied is as follows,
Figure FDA0003503635130000025
denotes an arbitrary value, δΘRepresenting a constant beam width constraint coefficient, f0Representing a reference frequency point in a constant beam width constraint,
Figure FDA0003503635130000026
to stop band constraint coefficient, δnormFor the robustness constraint coefficient, Θ is the subspace of interest, θΘFor each azimuthal angle within the space theta,
Figure FDA0003503635130000027
in the form of a sub-space of no interest,
Figure FDA0003503635130000028
is a space
Figure FDA0003503635130000029
Inner azimuth angle, omega, system operating bandwidth, fΩFor each frequency point within the bandwidth Ω, a (f, θ) is a LM × 1-dimensional steering vector written as:
Figure FDA00035036351300000210
Figure FDA00035036351300000211
al,m＝cos(2πfl/fs+2πfsin(θ)dm/C)，l＝0,1,...,L-1,m＝0,1,...,M-1
wherein C is the sound velocity in water, d is the array element spacing of the uniform linear array, fsFor the sampling rate, f and θ are parameter variables, at fΩ、f0And
Figure FDA00035036351300000212
θΘselecting.
4. The beam forming method suitable for the unmanned mobile platform to detect the naval vessel line spectrum according to claim 2, wherein the specific process of the adaptive adjustment of the weight vector of the time domain broadband beam former in the step (4) is as follows:
the minimum mean square error between the target line spectrum reference signal d (n) in the step (3) and the output y (n) of the time domain broadband beam former in the step (2) is:
ξ(W(n))＝E{|d(n)-y(n)|2}＝E{|d(n)-WT(n)X(n)|2}
wherein E { } represents the signal expectation, ξ (W (n))) represents the minimum mean square error of d (n) and y (n), and the minimization ξ (W (n)) is taken as a criterion to obtain an adaptive adjustment formula of a weight vector W (n):
W(n+1)＝W(n)+με(n)X(n)
where ∈ (n) ═ d (n) — (n) y (n) denotes a residual of the adaptation process, μ is an adaptation step size, and the weight vector W (n +1) at the next time is updated by an arithmetic expression.
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Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
USH108H (en) * 1985-10-15 1986-08-05 The Government Of The United States Radar doppler processor using a fast orthogonalization network
CN1831556A (en) * 2006-04-14 2006-09-13 武汉大学 Single satellite remote sensing image small target super resolution ratio reconstruction method
CN102043145A (en) * 2010-11-03 2011-05-04 中国科学院声学研究所 Rapid broadband frequency domain beamforming method based on acoustic vector sensor uniform linear array
CN102998660A (en) * 2012-11-26 2013-03-27 哈尔滨工程大学 Robustness multi-beam forming method in near field scope
CN103969626A (en) * 2014-05-20 2014-08-06 西安电子科技大学 Wideband digital wave beam forming method based on all-pass type variable fractional delay filter
CN104035064A (en) * 2014-06-05 2014-09-10 哈尔滨工程大学 Robust broadband steered minimum variance beam forming method suitable for any formation
CN104656074A (en) * 2014-12-26 2015-05-27 中国科学院声学研究所 Target detecting method of weighted robust broadband beam forming
CN105277934A (en) * 2015-09-24 2016-01-27 哈尔滨工程大学 Weak lien spectrum object passive detection method based on array
CN107179535A (en) * 2017-06-01 2017-09-19 东南大学 A kind of fidelity based on distortion towed array strengthens the method for Wave beam forming
CN107886068A (en) * 2017-11-10 2018-04-06 哈尔滨工程大学 A kind of unknown line spectrum object detection method based on time-space domain line enhancement device

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6603427B2 (en) * 2001-06-27 2003-08-05 Raytheon Company System and method for forming a beam and creating nulls with an adaptive array antenna using antenna excision and orthogonal Eigen-weighting

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
USH108H (en) * 1985-10-15 1986-08-05 The Government Of The United States Radar doppler processor using a fast orthogonalization network
CN1831556A (en) * 2006-04-14 2006-09-13 武汉大学 Single satellite remote sensing image small target super resolution ratio reconstruction method
CN102043145A (en) * 2010-11-03 2011-05-04 中国科学院声学研究所 Rapid broadband frequency domain beamforming method based on acoustic vector sensor uniform linear array
CN102998660A (en) * 2012-11-26 2013-03-27 哈尔滨工程大学 Robustness multi-beam forming method in near field scope
CN103969626A (en) * 2014-05-20 2014-08-06 西安电子科技大学 Wideband digital wave beam forming method based on all-pass type variable fractional delay filter
CN104035064A (en) * 2014-06-05 2014-09-10 哈尔滨工程大学 Robust broadband steered minimum variance beam forming method suitable for any formation
CN104656074A (en) * 2014-12-26 2015-05-27 中国科学院声学研究所 Target detecting method of weighted robust broadband beam forming
CN105277934A (en) * 2015-09-24 2016-01-27 哈尔滨工程大学 Weak lien spectrum object passive detection method based on array
CN107179535A (en) * 2017-06-01 2017-09-19 东南大学 A kind of fidelity based on distortion towed array strengthens the method for Wave beam forming
CN107886068A (en) * 2017-11-10 2018-04-06 哈尔滨工程大学 A kind of unknown line spectrum object detection method based on time-space domain line enhancement device

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
" 便携式多波束测深仪实时波束形成技术研究与实现";朱旭初;《硕士电子期刊》;20050115;全文 *
"A new beam-forming algorithm based on flank acoustic vector-sensor array sonar";Guolong Liang 等;《2009 International Conference on Wireless Communications & Signal Processing》;20091231;第1-5页 *
"ADC Bit Optimization for Spectrum- and Energy-Efficient Millimeter Wave Communications";Jinseok Choi 等;《2017 IEEE Global Communications Conference》;20171231;第1-6页 *

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