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Active Target Multistatic Receiver Critical Design Review

Active Target Multistatic Receiver Critical Design Review. Group D: Sam Buchanan Haiji Wang Robby Willer. System Overview. Link Budget Update – Antenna Data. Gain of airborne antenna array. Simulated ATMR antenna gain. Link Budget Update – Received Power. Old. New.

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Active Target Multistatic Receiver Critical Design Review

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  1. Active Target MultistaticReceiverCritical Design Review Group D: Sam Buchanan Haiji Wang Robby Willer

  2. System Overview

  3. Link Budget Update – Antenna Data Gain of airborne antenna array Simulated ATMR antenna gain

  4. Link Budget Update – Received Power Old New

  5. Signal Power and SNR at ADC

  6. Previous Receiver Board

  7. Receiver Board Modifications

  8. Receive Chain Multiplexing

  9. RF Functional Schematic

  10. Receiver Board Stackup

  11. RF Circuit Schematic #1

  12. RF Circuit Schematic #2

  13. RF Circuit Schematic #3

  14. RF Circuit Schematic #4

  15. RF Circuit Schematic #5

  16. RF Circuit Schematic #6

  17. FPGA Application (Sequential) 1 2 4 3 1 2 Key steps: Move to baseband (mix with NCO) Decimation Matched filtering Delays for data timing/triggering

  18. FPGA Application (Parallel)

  19. Digitization • Parallelization built into NI 5772 • Time interleaved sampling (TIS)

  20. NCO • Implement with Xilinx DDS compiler • 8 NCOs with different phase offsets • Calculate equivalent NCO phase increment

  21. NCO

  22. LPF + Downsample • Task: convolution in parallel • Subconvolutions on each channel, sum to produce coherent output

  23. Parallel Convolution

  24. Parallel Convolution

  25. Parallel Convolution Params: fs=1.6 GHz, f0=150MHz, f1=450MHz, t1=10us, p=8, d=4

  26. Parallel Convolution Params: fs=1.6 GHz, f0=150MHz, f1=450MHz, t1=10us, p=8, d=4

  27. Matched Filtering • Correlation filter • Use only the beginning of the LFM waveform as filter coefficients • Use parallel convolution as with LPF

  28. Matched Filtering • Complication: 4 correlators needed (filter coefficients complex) • FPGA only has 288 MACs available • Longer matched filter equates to greater processing gain (RFI resistance) • 64 tap matched filter -> 256 MACs • Only 38 available for LPF stage and other adders • Plan: Implement ATMR with shorter matched filter (32 taps) for demonstration

  29. Delays and Data Transfer • Transfer data to host in 64 bit unsigned quad blocks (16 bit samples) • Challenge: interleaving data properly

  30. Updated Risks • Complexity of FPGA application • Mitigation: work less on host software, more on FPGA • Lack of DSP resources on FPGA • Mitigation: arrange for a new FPGA to be ordered for deployment; plan to demonstrate with shorter filters

  31. Clock Section Block Diagram

  32. Power Analysis • 20 dBm output power

  33. Clock Synthesizer Schematic #1

  34. Clock Synthesizer Schematic #2

  35. Clock Synthesizer Schematic #3

  36. Clock Synthesizer Schematic #4

  37. Integrated Test Plan • Work with Dr. Paden to develop test plan • The anechoic chamber has been reserved for testing on May 5-6. • The 1UDAQ will function as the waveform generator for this testing.

  38. Extra Slides

  39. Parallel Convolution • Parallel convolution algorithm • Partition LPF impulse response into 8 subsequences • Convolve each impulse response subsequence with each data channel • Symmetry between the decimation factor and number of channels could reduce the number of subconvolutionsequences required to generate coherent output • 8 channels * 8 IR subsequences = 64 total • Sum output using constraints specified in a theorem for reconstruction

  40. Parallel Convolution Example • x = (1, 2, 3, 4); h = (1, 2, 3, 4) • (Example taken from http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=00363597&tag=1)

  41. Parallel Convolution Example • 2 parallel channels (p = 2)

  42. Parallel Convolution Example • Compute subconvolution sequences yij (total p2 = 4)

  43. Parallel Convolution Example • To find the nth term of the output y, apply the reconstruction theorem constraints:

  44. Parallel Convolution Example • Apply reconstruction theorem constraints for all values n where y is nonzero • Note: no decimation in this example • If we downsample the output by 2, the only sequences we need are y00 and y11

  45. Parallel Convolution Example • Illustration: downsample y by 2 and re-index n 0 1 2 3 y(n) 1 10 25 16 y00 y00(0) y00(1) y00(2) y11y11(0) y11(1) y11(2)

  46. Parallel Convolution • ATMR has 8 channels, decimates by 3 • Complication: p and the decimation factor are coprime • Need all 64 subconvolutions • Wiring, delays, and timing will be complicated • Implementation plan: keep a state variable, increment and transfer it between executions with a shift register n = 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 …

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