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![Page 1: Analysis of Low Frequency Phased Array Stations Dr. Nima Razavi-Ghods Dr. Eloy de Lera Acedo Cambridge AAVP 2010, 09/12/10 1.](https://reader036.fdocuments.us/reader036/viewer/2022062314/56649e875503460f94b8bb03/html5/thumbnails/1.jpg)
Analysis of Low Frequency Analysis of Low Frequency Phased Array Stations Phased Array Stations
Dr. Nima Razavi-GhodsDr. Eloy de Lera Acedo
Cambridge AAVP 2010, 09/12/10
1
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OverviewOverview
Phased array design parameters
AA-lo station configuration studies (regular vs. random)
Randomisation of elements
Simulations to compute TA and A/T(geometries, weighting, element types)
Future work and conclusions
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Factors Affecting Beam on the SkyFactors Affecting Beam on the Sky
Array size (fundamental limit on Aeff/Tsys) Array geometry (main and side-lobe profile)
◦ Fully filled grids (regular lattice)◦ Sparse or thinned grids◦ Truly randomised grids
Antenna element response (scan/polarisation response, matching, mutual coupling)
Operating frequency, processing bandwidth, integration time Weighting schemes (main beam and side-lobe profile)
◦ Spatial windows (e.g. Hamming, Gaussian, Kaiser)◦ Side-lobe profile control (e.g. Dolph-Chebyshev/Taylor, Fourier
design method)◦ Adaptive nulling
Back-end processing◦ Fully digital core (any weighting in single or multiple stages)◦ First level analogue (some limitations in response)
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Antenna Array GeometriesAntenna Array Geometries4
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Random Vs. RegularRandom Vs. Regular5
Sky (Haslam) Lat = 28.59S, Long = 115.45E Date: 01/01/2020, Time 19.33h
Triangular Lattice Beam10,000 elements, d = 0.8
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Random Vs. RegularRandom Vs. Regular6
Sky (Haslam) Lat = 28.59S, Long = 115.45E Date: 01/01/2020, Time 19.33h
Random Lattice Beam10,000 elements
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Randomised Array: AA-loRandomised Array: AA-lo7
d = /3 : 2
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Randomisation algorithmRandomisation algorithm8
1.4 1.6 1.8 2 2.2 2.4 2.60
200
400
600
800
1000
1200
1400
1600
1800mean = 1.45, std = 0.10
Fre
que
ncy
dmin (min)
0.8 1 1.2 1.4 1.6 1.8 2 2.20
100
200
300
400
500
600
700mean = 1.45, std = 0.22
Fre
que
ncy
dmin (min)
Fixed min. distance
Variable min. distance
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Simulations to compute Simulations to compute TTAA
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TA was analysed as the beam tracked 3 cold patches on the sky over four and half hours.
Array factor based simulations carried computed using NFFT.
AA-lo Station ~10k elements. 6 Geometries: regular,
triangular, sparse random, thinned, concentric rings, and fully random.
4 minimum inter-element separations: 0.5, 0.8, 1, 2.
3 Weights: Uniform, Taylor and Dolph-Chebyshev (SLL = 35 dB)
3 Element types.
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SKA AA-lo observable SkySKA AA-lo observable Sky10
Region 1: 09h07m12s 0000’46’’, Region 2: 04h03m36s -3448’00’’ Region 3: 04h45m00s -6100’00’’
R1
R2
R3
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Results for Results for TTAA: Region 1: Region 111
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Results for Results for TTAA: Region 2: Region 212
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Results for Results for A/TA/T: Region 1: Region 113
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Results for Results for A/TA/T: Region 2: Region 214
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Taylor Weighting (SLL = 35 dB)Taylor Weighting (SLL = 35 dB)15
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AA-lo Observable Sky
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Low Gain vs. High Gain Low Gain vs. High Gain ElementElement
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40 60 8033
33.5
34
34.5
35Regular Array (d = 0.5): Sensitivity @ 100 MHz
Local Sidereal Time /degrees (R2)
Aef
f/Tsy
s (m
2 /K)
40 60 8040
50
60
70
80
90
100Regular Array (d = 0.8): Sensitivity @ 100 MHz
Local Sidereal Time /degrees (R2)
Aef
f/Tsy
s (m
2 /K)
40 60 8020
40
60
80
100
120
140Regular Array (d = 1.0): Sensitivity @ 100 MHz
Local Sidereal Time /degrees (R2)
Aef
f/Tsy
s (m
2 /K)
Cosine2
CosineBow-tie
40 60 8042
43
44
45
46
47
48
49Random Array (d = 0.5): Sensitivity @ 100 MHz
Local Sidereal Time /degrees (R2)
Aef
f/Tsy
s (m
2 /K)
40 60 8030
40
50
60
70
80
90
100Random Array (d = 0.8): Sensitivity @ 100 MHz
Local Sidereal Time /degrees (R2)
Aef
f/Tsy
s (m
2 /K)
40 60 8030
40
50
60
70
80
90
100Random Array (d = 1.0): Sensitivity @ 100 MHz
Local Sidereal Time /degrees (R2)
Aef
f/Tsy
s (m
2 /K)
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Xarray Tool: MATLAB GUIXarray Tool: MATLAB GUIwww.mrao.cam.ac.uk/~nima/xwww.mrao.cam.ac.uk/~nima/x 18
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Future work and collaborationsFuture work and collaborations
Main objective: SKA simulatorFaster and more accurate simulations of
the station beam based on MBF approach (collaboration with UCL).
Computation framework for station simulator (collaboration with Oxford).
Further analysis of beam synthesis techniques and weight calibration.
Design of optimal geometry, e.g. far out versus close in side-lobes.
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Thank You.Thank You.
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