Figure 1: (a) Example of broadband continuous frequency content input: 18GHz gaussian pulse. (b) Example of broadband sparse frequency content input: simultaneous reception of three 10μs duration chirped pulses (fc=3.3GHz chirp=1MHz/μs, fc=10.5GHz chirp=1MHz/μs, fc=18.1GHz chirp=50MHz/μs).

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PHOTONIC MICROWAVE-TO-DIGITAL SUBSYSTEMS: WHEN, WHY AND HOW

Thomas R. Clark Jr.1, Patrick Callahan2, Sean R. O’Connor1, Dalma Novak1, and Michael L. Dennis2

1Pharad, LLC, Glen Burnie, MD USA 2The Johns Hopkins University Applied Physics Laboratory, Laurel, MD USA

Introduction The accurate collection and assessment of information contained in the electromagnetic (EM) environment is crucial to the success of a variety of avionic systems. The nature of the information to be collected and platform demanding multi-functionality requires these systems to simultaneously cover many RF and microwave bands and to deliver accurate (post-processed) information. Additionally, the increasing demands for higher system performance and increased versatility result in the reliance on digital signal processing (DSP) and consequently the high fidelity conversion of the analog microwave input signals to digital representations. In this paper, we seek to classify input waveforms representing the key classes of analog signals and identify desired output information classes. We will also provide guidance for matching recently demonstrated photonic microwave-to-digital architectures to the input waveform/output time-spectra reconstruction scenarios. In addition, we will cover the performance parameters and the crucial microwave-optical-electrical-digital interface issues.

Microwave Input Waveform Classes and Microwave-to-Digital Architectures Most broadband avionic input signals fall into two frequency content classes, those of broad continuous frequency content and those of sparse frequency content. The first class consists of single events or potentially distinct series of events, such as a radar pulse train or data communications, which may be of limited temporal extent or contain continuously changing information and therefore must be sampled during the finite time or else the signal and its information is lost. Figure 1(a) illustrates an example of the continuous broadband frequency content with a single 18 GHz RF pulse of 100% fractional bandwidth simulated. Here there exists no frequency content which would be accurately represented after a digital or analog filter of bandwidth < 30 GHz without significantly altering the signal information. Additionally, sampling intervals greater than ~28 ps run the risk of completely missing the event. Digital communications signals likewise cannot be represented, without loss of significant information, at asynchronous sample rates less than twice the data rate without a high probability of missing information bits. For many applications, a single RF aperture could be expected to receive a multitude

of microwave signals of total frequency content existing over many GHz, but with the crucial output information accurately represented by a much lower total bandwidth plus some identifying information about the RF carriers involved and temporal extent of the signal. This situation is depicted in Figure 1(b) and falls into the general category of a sparse signal. Here we have simulated an input consisting of three overlapped microwave pulses. The desired information would be expected to be contained in the identification of the carrier frequency, the temporal extent of the signal and the encoded content; in this case the individual chirped carrier functions, consisting of a total sum bandwidth of 520 MHz. The total input bandwidth for this receiver would be required to be > 15 GHz while the output digital

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3:15 PM – 12:15 PMTuE1 (Invited)

978-1-4244-5313-9/10/$26.00 ©2010 IEEE

Figure 2: Photonic Microwave-to-Digital Block Diagram

Photonic Preconditioning

Remote Encoding

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Detection, RF Conditioning

A/D and Digital Signal

Processing

Synchronous Clocking

RF Local Oscillator

reconstructed bandwidth would need only be > 520 MHz, corresponding to an input bandwidth:output bandwidth ratio > 28. For signals of sparse frequency content, the potential architectures can have asymmetric input:output bandwidths leading to more varied potential solutions including the common RF practice of channelized receivers.

Two of the principal advantages of photonic technology in microwave systems are the ability to receive broad bandwidths with a single hardware solution and to distribute the signal over lightweight, flexible, electromagnetically immune optical fiber. The ability to do this without unacceptable performance degradation has been mostly elusive. Recent advances in photonic systems, using design approaches concentrating on applying the benefits of photonics within the context of the entire microwave-to-digital chain and the intended input waveform/output information scenario have largely overcome, or shown significant potential to overcome, this performance degradation. Figure 2 illustrates a general block diagram for systems realizing these goals primarily through broadband remote encoding and photonic pre-encoding conditioning or post-encoding conditioning designed to take full advantage of the intended analog-digital converter and the availability of digital signal processing. Of interest in this talk will be those architectures utilizing photonic preconditioning including photonic sampling [1−3], effectively using photonic sampling and synchronous clocking as a broadband front-end sample-and-hold circuit and high performance RF links [4−6]; downconverting the microwave signals when necessary using RF local oscillators. In each of these architectures digital signal processing can be used to enhance performance and compensate for imperfect physical implementation allowing significantly relaxed component requirements and bringing significant future performance promise to near-term reality.

Conclusion The growing spectral demands of modern microwave avionic systems make photonics’ RF signal distribution capabilities, combined with the ability to accommodate severe size and weight constraints, likely to see significant technology insertion opportunities in the near future. Recent technology advances and a design approach cognizant of the full microwave-optical-electrical-digital chain will bring this prediction to reality.

Acknowledgements Some material is based on work supported by DARPA under DoD Award No. W911NF-08-1-0243.

References [1] P.W. Juodawlkis, J. C. Twitchell, G. E. Betts, J. J. Hargreaves, R. D. Younger, J. L. Wasserman, F. J. O’Donnell, K. G. Ray, and R. C. Williamson, “Optically sampled analog-to-digital converters”, IEEE Trans. Micro. Theory and Tech., vol. 49, no. 10, pp. 1840-1853, October 2001. [2] M. B. Airola, S. R. O’Connor, M. L. Dennis, and T. R. Clark, “Experimental demonstration of a photonic analog-to-digital converter architecture with pseudorandom sampling”, IEEE Photon. Tech. Lett., vol. 20, no. 24, pp. 2171-2173, December 2008. [3] G. A. Sefler, J. Chou, J. A. Conway and G. C. Valley, “Distortion correction in a high-resolution time-stretch ADC scalable to continuous time”, J. Lightwave Tech., vol. 28, no. 10, pp. 1468-1476, May 2010. [4] A. Karim and J. Devenport, “High dynamic range microwave photonic links for RF signal transport and RF-IF Conversion”, J. Lightwave Tech., vol. 26, no. 15, pp. 2718-2724, August 2008. [5] S. R. O’Connor, M. C. Gross, M. L. Dennis and T. R. Clark, “Experimental demonstration of RF photonic downconversion from 4-40 GHz”, IEEE Int. Topical Meeting on Microwave Photonics, paper Th3.2, October 2009. [6] T. R. Clark, S. R. O’Connor and M. L. Dennis, “A phase-modulation I/Q-demodulation microwave-to-digital photonic link”, invited submission to IEEE Micro. Theory and Tech. Special Issue on Microwave Photonics, November 2010.

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