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Design of Arrays minimizing Side Lobes

Design of Arrays minimizing Side Lobes. Leonid Kogan National Radio Astronomy Observatory. OUTLINE. Comparison of configuration figures-of-merit Which side lobes to optimize, positive or negative? Connection of the Point Spread Function to the Beam pattern.

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Design of Arrays minimizing Side Lobes

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  1. Design of Arrays minimizing Side Lobes Leonid Kogan National Radio Astronomy Observatory SPDO meeting

  2. OUTLINE • Comparison of configuration figures-of-merit • Which side lobes to optimize, positive or negative? Connection of the Point Spread Function to the Beam pattern. • Brief description of the algorithm. • AIPS tasks CONFI and UVCON • Examples of projects where arrays were designed using this side lobe minimizing algorithm SPDO meeting

  3. Configuration figures-of-merit. • Minimal side lobes • Gaussian shape of the main beam • Minimal gaps in the UV coverage • Others Optimizing figures of merit other than “Minimal side lobes” improves the side lobes level implicitly, but a direct minimal side lobes optimization may produce better results. SPDO meeting

  4. Which side lobes to optimize:Positive or Negative? SPDO meeting

  5. SPDO meeting

  6. Q1. In which direction should each array antenna be moved to decrease the value of the array Beam Pattern (Point Spread function - PSF)? • Q2. How far should each array antenna be moved to decrease the value of the array Beam Pattern (Point Spread Function - PSF) in that direction? SPDO meeting

  7. Where to move antennas? SPDO meeting

  8. How much should an array antenna move along the found direction? by The derivative of the function determines how far is the antenna from the optimum Therefore the required shift of the given antenna Is proportional to the relevant derivative: SPDO meeting

  9. The AIPS task CONFI CONFI can design an optimum configuration using an iterative method. During each iteration the direction of the biggest side lobe is computed. Then the algorithm of the described above is applied. Each antenna is moved by a small portion of the calculated value determined by a small (<<1) input parameter gain. Various parameters can be constrained, such as topography, minimum spacing, configuration bounds, several initial configurations. SPDO meeting

  10. List of some arrays optimized minimizing side lobes. • ALMA Atacama Large Millimeter Array. • SKA Square Kilometer Array (Antenna station) • EVLA. Most compact E-configuration • DSN 100 of 12 meter dishes • LWA: Long Wavelength Array. Antenna station of 256 dipoles each SPDO meeting

  11. An ALMA Largest Configuration Optimized with Matching the Terrain at the Chajnantor Site(Chile) SPDO meeting

  12. Alma compact configuration optimized having topography file of the roads.The side lobes optimized inside of a part of the primary beam.Maximum side lobe ~0.009 SPDO meeting

  13. LWA antenna station with 256 dipoles.Minimum spacing 2m. The area of optimization is the whole semi-sphere.The side lobes are less than 0.0056 (22.5dB) SPDO meeting

  14. Slice of the above beam pattern along DEC SPDO meeting

  15. Slice of the above beam pattern along RA SPDO meeting

  16. LWA antenna station with 256 dipoles.The beam pattern is phased toward zenith angle 60, azimuth 45. SPDO meeting

  17. EVLA compact configuration.The size of the dots (red are existing pads) shows the antennadiameter 25 meter. The side lobes are optimized inside of the primary beam. Maximum side lobe ~5%. SPDO meeting

  18. SKA antenna station example. The antenna diameter 12 meter. The side lobes are optimized inside of the primary beam. Maximum side lobe ~3% SPDO meeting

  19. DSN array120 of 12 meter dishesSide lobes ~25db SPDO meeting

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