Analysis of Low Frequency Phased Array Stations Dr. Nima Razavi-Ghods Dr. Eloy de Lera Acedo...

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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

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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)

Antenna Array GeometriesAntenna Array Geometries4

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

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

Randomised Array: AA-loRandomised Array: AA-lo7

d = /3 : 2

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

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.

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

Results for Results for TTAA: Region 1: Region 111

Results for Results for TTAA: Region 2: Region 212

Results for Results for A/TA/T: Region 1: Region 113

Results for Results for A/TA/T: Region 2: Region 214

Taylor Weighting (SLL = 35 dB)Taylor Weighting (SLL = 35 dB)15

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AA-lo Observable Sky

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

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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)

Xarray Tool: MATLAB GUIXarray Tool: MATLAB GUIwww.mrao.cam.ac.uk/~nima/xwww.mrao.cam.ac.uk/~nima/x 18

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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