Real-Time Differential Signal Phase Estimation for Space-Based Systems using FPGAs

Lu, Shiting (Justin); Siqueira, Paul; Vijayendra, Vishwas; Chandrikakutty, Harikrishnan Kumarapillai; Tessier, Russell

doi:10.1109/taes.2013.6494407

Cited by 13 publications

(6 citation statements)

References 12 publications

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“…Since the proposed frequency measurement system determines the incoming microwave signal frequency by measuring the signal phase differences, a phase detection error causes an error in frequency measurement. However, a phase detector can be made to have a high accuracy of better than 0.1 [23]. Hence the frequency measurement error caused by the phase detector detection error can be neglected.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…This agrees with the phase difference to time delay relationship stated in Section II. Phase detectors with an accuracy of better than 1 and a phase detection range of 0-360 have been reported [22], [23], [26]. Hence the input microwave signal frequency can be measured in high resolution by using these high-accuracy phase detectors in the proposed structure.…”

Section: Resultsmentioning

confidence: 99%

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Wideband High-Speed and High-Accuracy Instantaneous Frequency Measurement System

et al. 2023

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A new photonic-assisted instantaneous frequency measurement system is presented. It overcomes the latency problem in the reported structures based on the frequency-to-time mapping technique or the frequency-to-power mapping technique that involves a long length of fiber, and at the same time, enables the incoming microwave signal frequency to be measured over a wide frequency range with only small errors. The system generates three low-frequency signals. The phases of the three low-frequency signals are compared. One of the two low-frequency signal phase differences is used to estimate the incoming microwave signal frequency unambiguously over a wide frequency range and the other is used to provide accurate microwave signal frequency measurement. A proof-of-concept experiment is set up. Experimental results show, by measuring the phase difference of two low-frequency signals, the frequency of the input microwave signal can be determined unambiguously in 15 GHz and 500 MHz frequency ranges with errors below ±220 MHz and ±10 MHz respectively. Hence, by using two low-frequency signal phase differences, the input microwave signal frequency can be determined accurately over a wide frequency range. The new photonic-assisted frequency measurement system has a fast response time, which is an order of magnitude shorter than that of the systems based on the frequency-to-time mapping technique and the frequency-to-power mapping technique with a kilometer-long fiber.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Wideband High-Speed and High-Accuracy Instantaneous Frequency Measurement System

et al. 2023

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“…A digital phase detector (DPD) based on a fieldprogrammable gate array (FPGA) can be used to measure 0°−360°phase difference of the two low-frequency IF signals [19], [20]. Since the phase difference of the IF signal is twice the phase difference of the microwave signal received by two antennas and a DPD can detect a phase difference of 0°to 360°, a microwave signal phase difference of 0°to 180°can be detected.…”

Section: Analysis and Discussionmentioning

confidence: 99%

Photonic Frequency Down Conversion Approach to Measure Microwave Signal Angle of Arrival

Huang

Chan

2022

IEEE Photonics J.

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This paper presents an angle-of-arrival (AOA) measurement system based on microwave photonic frequency down conversion. It has the novelty of no LO is needed for the frequency conversion process. Instead, a ramp waveform is used to shift the frequency of an optical carrier, which is phase modulated by a microwave signal in the subsequent stage. Two low-frequency IF signals are generated after photodetection. The AOA of the incoming microwave signal can be determined by measuring the phase difference of the two IF signals. Comparing with the previously reported frequency converter based AOA measurement systems, the proposed structure does not need a high-frequency tunable LO source and high-frequency electrical components. Expensive and bulky equipment such as an electrical spectrum analyser are not required in the proposed AOA measurement system. Experimental results show AOA measurement of different-frequency and different-power microwave signals, with small measurement errors.

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“…Hardware cosimulation carried out on a Xilinx Spartan-3E board verified the performance of this FPGA-based preprocessing method. A phase estimation circuit was developed in [24], which was implemented on FPGA hardware and experimentally tested using a new state-of-the-art data acquisition system developed for the NASA SWOT project. This circuit is capable of detecting very small phase differences in time-varying analog signals.…”

Section: Introductionmentioning

confidence: 99%

Hardware implementation and comparison of displacement retrieval algorithms for a laser diode-based optical feedback interferometric sensor

Rehman¹,

Zabit²,

Ullah³

2018

Turk J Elec Eng & Comp Sci

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Optical feedback interferometer (OFI) lasers, also called self-mixing (SM) lasers, have been widely explored over the last couple of decades due to their low cost, compactness, and self-aligned nature and they provide a very good solution for measurements of displacement, vibration, distance, velocity, etc. The SM effect takes place when a part of the laser beam is fed back to the active laser cavity after reflecting from the target. The reflected beam interferes with the emitted beam and hence the optical and spectral characteristics of the laser get changed. To retrieve the vibration or displacement signal of the target from the SM signal, different postprocessing algorithms have been proposed, such as the phase unwrapping method (PUM). The first step of the PUM leads to the coarse estimation of the laser phase and the final step is an iterative joint estimation of 2 parameters, namely laser coupling coefficient C and linewidth enhancement factor α . To make this algorithm applicable for real-time measurements, parallel joint estimation for a wide range of C and α values needs to be done. In this research, 3 algorithms, namely PUM, direct fringe unwrapping (DFU), and improved DFU (IDFU) were tested for FPGA implementation by using Verilog HDL (hardware description language) so that more precise and real-time vibration and displacement signals of targets could be extracted from the SM sensor in an embedded systems environment. These algorithms were developed using Verilog HDL for implementation on the Xilinx Spartan-3 Xcs400-FG320 development board. Our designed IDFU algorithm performed 0.492 times better than the parallel PUM algorithm in maximum clock frequency and 1.53 and 1.21 times better than the PUM in slice registers and LUT utilization of hardware resources, respectively. The designed DFU algorithm can operate 1.355 times better than IDFU in maximum clock frequency and 25.34 and 14.25 times better than IDFU in slice registers and LUT utilization of hardware resources, respectively.

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Real-Time Differential Signal Phase Estimation for Space-Based Systems using FPGAs

Cited by 13 publications

References 12 publications

Wideband High-Speed and High-Accuracy Instantaneous Frequency Measurement System

Wideband High-Speed and High-Accuracy Instantaneous Frequency Measurement System

Photonic Frequency Down Conversion Approach to Measure Microwave Signal Angle of Arrival

Hardware implementation and comparison of displacement retrieval algorithms for a laser diode-based optical feedback interferometric sensor

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