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First results of the PAU Synthetic Aperture Radiometer

First results of the PAU Synthetic Aperture Radiometer I. Ramos-Perez, G. Forte. X. Bosch- Lluis , E. Valencia, N. Rodriguez-Alvarez, H. Park, M. Vall·llossera , and A. Camps E-mail: isaacramos@tsc.upc.edu Remote Sensing Lab Universitat Politècnica de Catalunya (UPC) – Barcelona, Spain

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First results of the PAU Synthetic Aperture Radiometer

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  1. First results of the PAU Synthetic Aperture Radiometer I. Ramos-Perez, G. Forte. X. Bosch-Lluis, E. Valencia, N. Rodriguez-Alvarez, H. Park, M. Vall·llossera, and A. Camps E-mail: isaacramos@tsc.upc.edu Remote Sensing Lab UniversitatPolitècnica de Catalunya (UPC) – Barcelona, Spain and IEEC-CRAE/UPC 28th of July of 2011

  2. Outline • Review of PAU-SA instrument • Potential improvements for future SMOS – like missions • Use of PRN Signals for: Calibration, FWF Determination, and receiver’s frequency response determination • Inter-calibration phase determination in post-processing and real-time systems • Some Imaging results: • Impulse response (near field) • Angular resolution (near field) • GPS satellites constellation • Conclusions

  3. PAU-RAD PAU-GNSS-R PAU-IR 1. PAU-SA Instrument 8 m PAU-SA in the robotic arm

  4. 2. Potential improvements for future SMOS’s

  5. 3.1. Use of PRN Signals for: FWF determination Centralized Calibration using: Noise Source or PRN sequences FWF(Y1Y2) SR=0.5 • Overcomes limitations of centralized noise injection • PRN with SR > 5 (flat spectrum such as Noise Source) • Estimation of FWF at =0 with 1B/2L • Amplitude error < 0.25% • Phase error < 1º SR=1 I. Ramos-Pérez et al., “Use of Pseudo-Random Noise sequences in microwave radiometer calibration”, MICRORAD 2008 I. Ramos-Pérez et al., “Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals” Sensors 2009 ISSN 1424-8220 SR=5

  6. 3.2. Use of PRN Signals for: Receiver’s frequency response Using: PRN sequences Correlation of receivers’ output with local replica of PRN signal injected allows individual frequency responses to be measured (amplitude and phase) SPRN+SR1 A SPRN+SR2

  7. 4.1. Inter-calibration time in real-time systems Data: PAU-SA instrument Measurement: τ=1 s., every 2 min Off-line Processing  Decimate to simulate lack of data EKF INTERPOLATION ERROR: No aliasing • Best interpolation Methods: • Linear • Pchip • Spline • fft B ~ 1 mHz Tinter-cal max = 1 / 2·B ~ 4 min If Tinter-cal> 4 min Aliasing interpolation phase error Decimation factor 4 (8 min) Real-time Processing  Prediction, e.g. with Extended Kalman filter (EKF) Conclusion: Real-time systems require much more often calibration time to avoid estimation errors to propagate and increase rapidly

  8. 4.2. Inter-calibration time in off-line systems: SMOS Data: SMOS (L1 level)Commissioning Phase Measurement: τ=1.2 s., every 2 min Decimation Interpolation with different methods No aliasing  Optimum inter-calibration time • Best interpolation Methods: • fft • Interp (Sinc) • Spline • Max inter-calibration ~7 min • (decimation factor ~ 3.5) Optimum interpolation All visibilities (fft interpolation) B ~ 1.25 mHz Tinter-cal max = 1 / 2·B ~ 7 min If Tinter-cal> 7 min Aliasing interpolation phase error • At present: 10 min,~ 1º • But at ~7 min, < 0.3º • And << 7 min, marginal • improvement in 

  9. 5.1. Preliminary results (i): Impulse response Rectangular window for visibility samples Az +/- 10º, +/- 20º PRN Signal FFT Instrument El +/- 10º, +/- 20º Antenna 1 Pol H Az= 0º El= 0º Pol H Az= +10º El= 0º Pol H Az= +20º El= 0º PRN Source 1 Point Source : PRN signal (-70 dBm) Moving the Instrument (no temperature control) Pol V Az= 0º El= +10º Pol V Az= 0º El= +20º

  10. 5.2. Preliminary results (ii): Angular resolution 2 m 1 m 3 m 4 m Rectangular window FFT 2 PRN Signals Antennas separation at: Instrument Antenna 1 Antenna 2 PRN Source 1 PRN Source 2 Point Source: PRN signals (-70 dBm) 7 antennas per arm + rectangular window Sources – PAU-SA distance at 10 m Angular resolution (ξ,η) ~ 5.7º (Near field) No near-to-far field transformation applied

  11. 5.3. Preliminary results (iii): GPS satellites K K UTC 11:38:03 UTC 12:00:03 K K UTC 12:44:03 UTC 12:22:03 Rectangular window GPS Signal FFT GPS orbit UPC location

  12. 5.4. Preliminary results (iv): GPS satellites K

  13. 6. Summary • PAU-SA Instrument and design drivers briefly described • Successful test of use of PRN signals instead of noise for: Calibration, FWF, and receiver’s frequency response measurement • Optimum phase inter-calibration for off-line and real-time instruments. • Real-time processing (PAU-SA): due to a thermal drift, best results using: linear, pchip (piece wise cubic), spline, and fft interpolation techniques (inter-calibration time ~ 4 min) • Off-line processing (SMOS): Best results using: FFT or sincinterp, and reducing inter-calibration time ~ 7 min. • EKF to estimate phase evolution in a real-time system (PAU-SA)  larger error  more frequent calibration required (~ 1 min) • Image reconstruction using different PRN sources • Impulse response (one source in different positions of FOV) • Angular resolution(two sources with different angular separation)  ~ 0.1 • Zenith imaging of real GPS satellites:tracking GPS constellation

  14. Mr. Isaac Ramos Responsible for the design and manufacturing of the instrument Thank you!

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