KR101683827B1 - Low-Complexity Sliding-Vector based Apparatus and Method with Sampling Technique for Direction-of-Arrival Estimation with Uniform Linear Array Antenna Systems - Google Patents

Low-Complexity Sliding-Vector based Apparatus and Method with Sampling Technique for Direction-of-Arrival Estimation with Uniform Linear Array Antenna Systems Download PDF

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KR101683827B1
KR101683827B1 KR1020150113783A KR20150113783A KR101683827B1 KR 101683827 B1 KR101683827 B1 KR 101683827B1 KR 1020150113783 A KR1020150113783 A KR 1020150113783A KR 20150113783 A KR20150113783 A KR 20150113783A KR 101683827 B1 KR101683827 B1 KR 101683827B1
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vector
arrival angle
dimension
extracted
linear array
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유도식
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홍익대학교 산학협력단
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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01Q—ANTENNAS, i.e. RADIO AERIALS
    • H01Q3/00—Arrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an antenna or antenna system
    • H01Q3/26—Arrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an antenna or antenna system varying the relative phase or relative amplitude of energisation between two or more active radiating elements; varying the distribution of energy across a radiating aperture
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01Q—ANTENNAS, i.e. RADIO AERIALS
    • H01Q21/00—Antenna arrays or systems
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01Q—ANTENNAS, i.e. RADIO AERIALS
    • H01Q3/00—Arrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an antenna or antenna system
    • H01Q3/26—Arrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an antenna or antenna system varying the relative phase or relative amplitude of energisation between two or more active radiating elements; varying the distribution of energy across a radiating aperture
    • H01Q3/2605—Array of radiating elements provided with a feedback control over the element weights, e.g. adaptive arrays

Abstract

The present invention relates to a method of estimating the arrival angle of K signal sources incident on a linear array antenna system, characterized in that when N antenna sensors of at least 2K or more are installed with a constant sensor distance d , N determining a first step of tie output signals to generate the same N-dimensional output signal column vector x (t) of the number of output signals with a sampling interval δ i 1 and the start point and the amount more than 2 K -1 complex dimension Lc a second step up to the overlapping factor and the same number and the composite dimension Lc of the step of selecting the M selecting a constant correlation between the sample r 1, r 2, r 3 , ..., a fourth obtaining a r Lc A second step of generating a complex column vector r by grouping the correlation samples r 1 , r 2 , r 3 , ..., r Lc and a fifth step of setting the value of the extracted dimension L to K or more and Lc -K + 1 Subordinate And the elements of the complex column vector r are successively grouped into L extraction dimensions L to obtain K extracted column vectors

Figure 112015078146961-pat00093
,
Figure 112015078146961-pat00094
,
Figure 112015078146961-pat00095
, ...,
Figure 112015078146961-pat00096
And a sixth step of generating the extracted column vector
Figure 112015078146961-pat00097
,
Figure 112015078146961-pat00098
,
Figure 112015078146961-pat00099
, ...,
Figure 112015078146961-pat00100
Are extracted through Gram-Schmidt Orthonormalization (Gram-Schmidt regularization)
Figure 112015078146961-pat00101
,
Figure 112015078146961-pat00102
,
Figure 112015078146961-pat00103
, ...,
Figure 112015078146961-pat00104
And a seventh step of obtaining the extracted orthonormal vector
Figure 112015078146961-pat00105
,
Figure 112015078146961-pat00106
,
Figure 112015078146961-pat00107
, ...,
Figure 112015078146961-pat00108
To obtain an objective function f (&thetas;) using the objective function f (&thetas;),
Figure 112015078146961-pat00109
And a ninth step of estimating the arrival angle of the low-complexity linear array based on the sliding vector based on the sampling technique. The proposed algorithm is similar to the conventional low-complexity high-performance arrival angle estimation method, Each estimation performance is enabled. In addition, the linear array arrival angle estimation method and apparatus of the present invention can estimate the arrival angle quickly by further reducing the complexity by increasing the sampling interval or the sampling dimension by a simple setting according to the environment for estimating the arrival angle , It is possible to remarkably increase the arrival angle estimation performance by reducing the sampling interval or increasing the extraction dimension.

Description

(Low-Complexity Sliding-Vector Based Apparatus and Method with Sampling Technique for Direction-of-Arrival Estimation with Uniform Linear Array Antenna Systems)

The present invention relates to a method and apparatus for estimating the angle of incidence of an incoming signal, and more particularly to a method and apparatus for estimating the angle of incidence of an incoming signal, and more particularly, to a method and apparatus for estimating the angle of arrival of a signal entering an equidistant linear array antenna system. DOA) using a sampling technique and an apparatus therefor.

Generally, a beam forming algorithm is applied to estimate the arrival angle of a signal incident on an antenna. However, this method is difficult to estimate accurately when two or more signals arrive from adjacent directions because the estimation performance of the arrival angle is low. R. O. Schmidt (Non-Patent Document 1 of the prior art reference) proposed a MUSIC (multiple signal classification) technique that can fundamentally overcome the limitations of such a decomposition performance. However, the MUSIC scheme requires a process such as eigenvalue decomposition with a high complexity despite the advantage of high resolution. In order to overcome the complexity problem described above, N. Xi and L. Liping proposed a new arrival angle estimation technique which shows relatively high performance without requiring the process of eigenvalue decomposition in 2014. However, the Xi and Liping techniques are far superior to the beamforming algorithm, but have a problem in that they do not meet the performance of the MUSIC technique.

Korean Registered Patent No. 10-1274554 (June 3, 2013)

 IEEE Trans. Antennas Propagation, Multiple Emitter Location and Signal Parameter Estimation: Schmidt, R. O., 1986, Vol.34, ISSN: 0018-926X, 276-280  IEEE Signal Process. Lett. A Computationally Efficient Subspace Algorithm for 2-D DOA Estimation with L-shpaed Array: Xi, N. and Liping, L., 2014, Vol.21, ISSN: 1070-9908, 971-974

In the conventional low-complexity, high-performance estimation technique (Non-Patent Document 2), a cross-correlation between signals observed in two linear arrays constituting an L-shape is used by using an L-shaped array. Although this method can achieve a very low complexity, it is worse in performance than a technique using self-correlation such as MUSIC (multiple signal classification). We aim to provide a low-complexity, uniform-linear-array-arrival-angle estimation method and apparatus which have a low complexity similar to the technique disclosed in Non-Patent Document 2 by using a self-correlation sampling technique, do.

In order to accomplish the object, there is provided a method of estimating an arrival angle of K signal sources incident on a linear array antenna system, wherein when N antenna sensors of at least 2K or more are installed with a constant sensor distance d , the first step to tie the N output signals as measured by the sensor to produce an output signal column vector x (t) of the same N-dimensional to the number of output signals with a sampling interval δ and 2 K determines the starting point i 1 and the compound D Lc a second step of selecting as a positive integer not less than -1 and the maximum overlapping the acquisition sample r 1, r 2, correlated with the same number and the composite dimension Lc of the method for selecting the 3 r M 3, ..., r and the fourth step and the correlation of the sample to obtain the relationship Lc r 1, r 2, r 3, ..., r Lc to tied the value of the fifth step and the extracted dimension L to generate a complex column vector r over K, Lc- K + 1 or less And the elements of the complex column vector r are successively grouped into L extraction dimensions L to obtain K extracted column vectors

Figure 112015078146961-pat00001
,
Figure 112015078146961-pat00002
,
Figure 112015078146961-pat00003
, ...,
Figure 112015078146961-pat00004
A sixth step of generating the extracted column vector
Figure 112015078146961-pat00005
,
Figure 112015078146961-pat00006
,
Figure 112015078146961-pat00007
, ...,
Figure 112015078146961-pat00008
Are extracted through Gram-Schmidt Orthonormalization (Gram-Schmidt regularization)
Figure 112015078146961-pat00009
,
Figure 112015078146961-pat00010
,
Figure 112015078146961-pat00011
, ...,
Figure 112015078146961-pat00012
And a seventh step of obtaining the extracted orthonormal vector
Figure 112015078146961-pat00013
,
Figure 112015078146961-pat00014
,
Figure 112015078146961-pat00015
, ...,
Figure 112015078146961-pat00016
To obtain an objective function f (&thetas;) using the objective function f (&thetas;),
Figure 112015078146961-pat00017
And a ninth step of estimating the arrival angle of the vehicle.

As described above, there is an effect that remarkably improved arrival angle estimation performance can be achieved while maintaining a similar level of complexity in comparison with existing low complexity high performance arrival angle estimation techniques. In addition, the linear array arrival angle estimation method and apparatus of the present invention can estimate the arrival angle quickly by further reducing the complexity by increasing the sampling interval or the sampling dimension by a simple setting according to the environment for estimating the arrival angle , It is possible to remarkably increase the arrival angle estimation performance by reducing the sampling interval or increasing the extraction dimension.

FIG. 1 is a flowchart showing an approach angle estimation method in a conventional array antenna system. FIG.
FIG. 2 is a flow diagram of a sliding vector-based low-computed constant-interval linear array arrival angle estimation method using a sampling technique according to the present invention.
FIG. 3 is a conceptual diagram of a sliding-vector-based low-computed constant-interval linear array arrival angle estimation method using a sampling technique according to the present invention.
FIG. 4 is a simulation graph of a low-complexity constant-interval linear array arrival-angle estimation method based on a sliding vector using a sampling technique according to the present invention.

FIG. 2 is a flow chart of a method of estimating an angle of arrival of an array of low-computed equidistant linear arrays based on a sliding vector using a sampling technique according to the present invention.

A method for estimating an arrival angle of K signal sources incident on a linear array antenna system, comprising the steps of: when N antenna sensors (12) of at least 2K or more are installed with a predetermined sensor distance d (13) A first step (S10) of combining the N output signals 11 observed by the antenna sensor 12 to generate an N- dimensional output signal column vector x (t) 10 equal to the number of the output signals 11; and 2, 3, ..., 2N- 1 for determining a value of the sampling interval δ (21) and the crystals 1, 2, ..., N- 1 as the starting point the value of one of i 1 (22) of the but, the starting point i 1 (22) is of the N- and i 1 is selected so that it does not fall into the sampling interval δ (21) described above, the composite dimension Lc (20) δ Lc ≤ 2N + δ- i 1 -1 and (S20) for selecting an integer satisfying an expression of Lc & amp; ge; 2K-1 and a positive integer less than 1/2 of the complex dimension Lc (20) as a maximum overlapping factor M Step 3 (S30); if the k≤NM, Equation 1 below, k> NM of the case, to the correlation between samples of the same number and the composite level Lc (20) respectively using Equation 2 r 1 , r 2, r 3, ... , r Lc fourth step to obtain (40) (S40); and wherein the samples of the correlation r 1, r 2, r 3 , ..., r Lc (40) tie complex column vector r (50) a fifth step of generating (S50); and K or more and a compound establish the value of the extracted dimension L (61) to not more than Lc -K + 1 positive integers the column vector r (50 ) Are successively grouped by the number of extraction dimensions L (61) to obtain K extracted column vectors

Figure 112015078146961-pat00018
,
Figure 112015078146961-pat00019
,
Figure 112015078146961-pat00020
, ...,
Figure 112015078146961-pat00021
(S60) of generating the extracted column vector (60)
Figure 112015078146961-pat00022
,
Figure 112015078146961-pat00023
,
Figure 112015078146961-pat00024
, ...,
Figure 112015078146961-pat00025
(60) are extracted through Gram-Schmidt Orthonormalization (Gram-
Figure 112015078146961-pat00026
,
Figure 112015078146961-pat00027
,
Figure 112015078146961-pat00028
, ...,
Figure 112015078146961-pat00029
A seventh step S70 of obtaining the extracted orthonormal vector 70,
Figure 112015078146961-pat00030
,
Figure 112015078146961-pat00031
,
Figure 112015078146961-pat00032
, ...,
Figure 112015078146961-pat00033
(S80) of obtaining an objective function f ([theta]) (80) by using the equation (70); And the objective function f (&thetas;) (80)
Figure 112015078146961-pat00034
And a ninth step S90 of obtaining a minimum value 90 of the uniformly spaced linear array arrival angle based on the sliding vector.

Figure 112015078146961-pat00035
&Quot; (1) "

Figure 112015078146961-pat00036
&Quot; (2) "

The above sampling interval ? (21) occurs when the selectable range of the complex dimension Lc (20) is reduced when the value is increased. Therefore, the sampling interval ? (21) is selected as a relatively small numerical value such as 2 or 3 for optimal arrival angular estimation performance, and is selected as a larger integer value only for the purpose of lowering the complexity.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings. FIG. 3 is a conceptual diagram of a method for estimating an angle of arrival of an array of equally spaced linear array based on a sliding vector using a sampling technique of an autocorrelation matrix according to the present invention, where the number of antenna sensors 12 is N , Let K be the number. The antenna sensor 12 is installed with the same sensor distance d13. At this time, the K incident signals 14 incident on the antenna sensor 12 have a constant incident angle 15. It is an object of the present invention to provide a method and an apparatus for estimating the arrival angle of an incident signal (14) through the antenna sensor (12).

FIG. 2 is a flow chart of a method for estimating an angle of arrival of an array of low-computed equidistant linear arrays based on a sliding vector using a sampling technique of an autocorrelation matrix according to the present invention.

The present invention operates only when the number K of incident signals 14 is smaller than the extraction dimension L 61. Therefore, in the second step S20, the sampling interval ? 21 and the starting point i 1 (22) The dimension Lc (20) should be selected to satisfy the following equations (3) and (4).

Lc & gt; 2K-1 < EMI ID =

δ Lc ≤ 2N + δ- i 1 -1 < Equation 4>

The complex column vector r (50) generated in the fifth step (S50) is defined as the following equation (5).

Figure 112015078146961-pat00037
Equation (5)

The detailed description of the sixth step S60 is as follows. First, the correlation samples r 1 , r 2 , r 3 , ..., r L of the extraction dimension L (61) are grouped,

Figure 112015078146961-pat00038
And then r 2 , r 3 , r 4 , ..., r L +1 are combined to form an extracted column vector
Figure 112015078146961-pat00039
Generated and continue to bind to K r, r +1 K, +2 K r, ..., r L + K-1 a column vector extraction
Figure 112015078146961-pat00040
(60).

In order to generally improve the arrival angle estimation performance, Lc- K + 1 , which is the maximum value that can be selected by the value of the extraction dimension L (61), is selected. On the other hand, when the complexity is minimized, the value of the extraction dimension L (61) may be selected to be equal to the number K of incident signals. The extracted column vector

Figure 112015078146961-pat00041
(k = 1, 2, 3, ..., K) is given by Equation (6) below.

Figure 112015078146961-pat00042
&Quot; (6) &quot;

In addition, the Gram-Schmidt Orthonormalization performed in the seventh step S70 is a well-known technique, and a detailed description thereof will be omitted.

In the seventh step S70,

Figure 112015078146961-pat00043
(60) by applying the Gram-Schmidt regularized edification to the extracted orthonormal vector
Figure 112015078146961-pat00044
,
Figure 112015078146961-pat00045
,
Figure 112015078146961-pat00046
, ...,
Figure 112015078146961-pat00047
(70).

In the eighth step S80, the extraction regularization vector

Figure 112015078146961-pat00048
,
Figure 112015078146961-pat00049
,
Figure 112015078146961-pat00050
, ...,
Figure 112015078146961-pat00051
(70) is substituted into the following equation (7) to obtain an objective function f (?) (80).

Figure 112015078146961-pat00052
&Quot; (7) &quot;

Here ,? (?) Represents the column vector of the following equation (8 ) , where? Represents the wavelength of the input signal 14.

Figure 112015078146961-pat00053
&Quot; (8) &quot;

Thereafter, in the ninth step S90,

Figure 112015078146961-pat00054
To
Figure 112015078146961-pat00055
in
Figure 112015078146961-pat00056
Up to a certain distance, and K of each arrival estimates that a peak value in going to change at random intervals objective function f (θ) (80)
Figure 112015078146961-pat00057
(90). The above-
Figure 112015078146961-pat00058
(90)
Figure 112015078146961-pat00059
.

The simulation results of the sliding-vector-based low-calculation-equal-interval linear array arrival angle estimation method using the sampling scheme constructed as described above will be described with reference to FIG.

4 shows an example in which the incident angle 15 is greater than or equal to 60 using an output signal 11 observed at twenty antenna sensors 12 with a sensor interval d of ¼ of the input signal 14 wavelength λ. 0, 80, 100 and 120, respectively. 4, the x-axis represents the signal-to-noise ratio (dB of the signal to noise ratio) and the y-axis represents the root mean square error. A graph of FIG. 4 uses the prior art of the non- And the graph B shows the results obtained by using the sliding vector-based low-calculation-equal-interval linear array arrival angle estimation method using the sampling technique according to the present invention. A and B graphs in FIG. 4 are compared It can be seen that the result using the present invention can be used at a significantly lower signal to noise ratio than that of the prior art and maintains a lower error even at a high signal to noise ratio have.

Although the present invention has been shown and described with respect to specific embodiments and applications thereof, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. Anyone with knowledge will know easily.

10. Output signal column vectorx (t) 11. Output signal
12. Antenna sensor 13. Sensor intervald
14. Incident signal 15. Incident angle
20. Complex DimensionLc 21. Sampling intervalδ
22. Starting point i One 30. Maximum redundancy factor M
40. Correlation Samplesr One ,r 2 ,r 3 , ...,r Lc 50. Complex Column Vector r
60. Extraction column vector

Figure 112015078146961-pat00060
,
Figure 112015078146961-pat00061
,
Figure 112015078146961-pat00062
, ...,
Figure 112015078146961-pat00063
61. Extraction dimensionL
70. Extraction regularization vector
Figure 112015078146961-pat00064
,
Figure 112015078146961-pat00065
,
Figure 112015078146961-pat00066
, ...,
Figure 112015078146961-pat00067
80. Objective functionf (?)
90. Estimated angle of arrival
Figure 112015078146961-pat00068
S10. Step 1
S20. Second step S30. Step 3
S40. Fourth step S50. Step 5
S60. Step 6 S70. Step 7
S80. Step S90. Step 9

Claims (6)

A method for estimating an arrival angle of K signal sources incident on a linear array antenna system by an arrival angle estimating apparatus,
When N antenna sensors 12 of at least 2K or more are installed with a predetermined sensor interval d 13, N output signals 11 observed by the antenna sensor are grouped and N A first step (SlO) of generating an output signal sequence vector x (t)
2, 3, ..., 2 N -1 determines the values of one sampling interval δ (21) and the crystals 1, 2, ..., N- 1 as the starting point the value of one of i 1 (22) of the (1) is selected so that N i 1 is not divided by the above sampling interval δ (21), and a complex dimension Lc (2) is selected as an integer satisfying the equations of δ Lc ≤ 2N + δ- i 1 -1 and Lc ≥ 2K- 20); and
A third step (S30) of selecting one of positive integers less than 1/2 of the complex dimension Lc (20) as the maximum overlap factor M (30);
If k &lt;
Figure 112015078146961-pat00069
, Where k &gt; NM,
Figure 112015078146961-pat00070
Correlation sample to the expression of each using the same number of the composite dimension Lc (20) of the r 1, r 2, r 3 , Step 4 to obtain ..., r Lc (40) ( S40); and
The correlated samples r 1, r 2, r 3 , ..., r Lc (40) a complex column vector a fifth step (S50) of generating r (50) tie; and
K or more and the extracted dimension L (61) establish a value enclosed by the number of the extracted dimension L (61) the elements of the complex column vector r (50) of the sequential extraction of the K a positive integer less than or equal to Lc -K + 1 Column vector
Figure 112015078146961-pat00071
,
Figure 112015078146961-pat00072
,
Figure 112015078146961-pat00073
, ...,
Figure 112015078146961-pat00074
(S60) of generating a second image (60); and
The extracted column vector
Figure 112015078146961-pat00075
,
Figure 112015078146961-pat00076
,
Figure 112015078146961-pat00077
, ...,
Figure 112015078146961-pat00078
(60) are extracted through Gram-Schmidt Orthonormalization (Gram-
Figure 112015078146961-pat00079
,
Figure 112015078146961-pat00080
,
Figure 112015078146961-pat00081
, ...,
Figure 112015078146961-pat00082
A seventh step S70 of obtaining the second image 70;
The above-described extraction regularization vector
Figure 112015078146961-pat00083
,
Figure 112015078146961-pat00084
,
Figure 112015078146961-pat00085
, ...,
Figure 112015078146961-pat00086
(S80) of obtaining an objective function f ([theta]) (80) by using the equation (70); And
Through the objective function f (&amp;thetas;) (80)
Figure 112015078146961-pat00087
And a ninth step (S90) of obtaining an estimated value 90 of the uniformly spaced linear array arrival angle based on the sliding vector. The method according to claim 1,
(20) to the third step (S30) when the number K of incident signals (14) is equal to or less than 1/2 of the number obtained by adding 1 to the complex-dimensional Lc (20) A Low - Computed Equal - Spacing Linear Array Arrival Angle Estimation Method Based on Sliding. The method according to claim 1,
The complex column vector r (50)
Figure 112015078146961-pat00088
And calculating a sliding distance of the array based on the sampling vector. The method according to claim 1,
The extracted column vector
Figure 112016069104517-pat00114
(60)
Figure 112016069104517-pat00090
And calculating a sliding distance of the array based on the sampling vector. The method according to claim 1,
The objective function f (θ) (80) when λ is one wavelength of the input signal 14 row vector α (θ) =
Figure 112015078146961-pat00091
Lt; RTI ID = 0.0 &gt;
Figure 112015078146961-pat00092
And calculating a sliding distance of the array based on the sampling vector. 1. An apparatus for estimating an arrival angle of signal sources incident on a linear array antenna system,
The sliding vector-based low-computed constant-interval linear array arrival angle estimating apparatus according to any one of claims 1 to 5, wherein the arrival angle is estimated.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108647418A (en) * 2018-05-03 2018-10-12 华中科技大学 A kind of synthetic aperture radiometer antenna array arrangement method that signal noise ratio (snr) of image is optimal

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002243826A (en) * 2000-12-12 2002-08-28 Matsushita Electric Ind Co Ltd Device and method for estimating arrival direction of radio wave and directivity variable transmitter/ receiver
JP2011053056A (en) * 2009-09-01 2011-03-17 Fujitsu Ltd Apparatus for estimating direction of arrival and method thereof
KR101274554B1 (en) 2012-03-02 2013-06-13 국방과학연구소 Method for estimating direction of arrival and array antenna system using the same
KR101375425B1 (en) * 2013-02-28 2014-03-17 충북대학교 산학협력단 Method for estimating direction of arrival in antenna array

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002243826A (en) * 2000-12-12 2002-08-28 Matsushita Electric Ind Co Ltd Device and method for estimating arrival direction of radio wave and directivity variable transmitter/ receiver
JP2011053056A (en) * 2009-09-01 2011-03-17 Fujitsu Ltd Apparatus for estimating direction of arrival and method thereof
KR101274554B1 (en) 2012-03-02 2013-06-13 국방과학연구소 Method for estimating direction of arrival and array antenna system using the same
KR101375425B1 (en) * 2013-02-28 2014-03-17 충북대학교 산학협력단 Method for estimating direction of arrival in antenna array

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
IEEE Signal Process. Lett. A Computationally Efficient Subspace Algorithm for 2-D DOA Estimation with L-shpaed Array : Xi, N. and Liping, L., 2014, Vol.21, ISSN : 1070-9908, 971-974쪽
IEEE Trans. Antennas Propagation, Multiple Emitter Location and Signal Parameter Estimation : Schmidt, R. O., 1986, Vol.34, ISSN : 0018-926X, 276-280쪽

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108647418A (en) * 2018-05-03 2018-10-12 华中科技大学 A kind of synthetic aperture radiometer antenna array arrangement method that signal noise ratio (snr) of image is optimal

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