The objective of this work was to develop a robust, cost-effective receiver with maximum dynamic range to track the frequency and power variation of a beacon signal. The result was the development of a frequency estimation algorithm that yields a more accurate measurement of frequency and signal power than conventional approaches like a simple FFT (fast Fourier transform) peak search with bin summing, or a phase locked loop (PLL).
A radio beacon is a radio frequency (RF) signal that is used to mark a location and usually transmits little or no data. Beacons have a wide variety of applications in areas such as tracking, navigation, mapping, and calibration. For example, spacecraft often carry RF beacons that are used by ground stations to locate and track the craft. Stationary ground-based beacons can be used in air and sea navigation equipment to find a relative bearing. Beacons can also be measured in terms of their power, frequency, phase delay, etc. to characterize the propagation of radio waves through the atmosphere.
In most beacon receiver applications, the received power of the beacon signal is a fundamental measurement. It can be used to locate the beacon by finding the direction of maximum power, as well as to measure the attenuation of the link by comparing the received power to the maximum power measurement in clear conditions. However, the frequency of the acquired beacon signal will often exhibit some drift, either due to the transmitter/ receiver hardware, or to Doppler shifts from a moving platform. As the frequency drifts continuously, it is necessary to accurately track the beacon frequency if an accurate measurement of its power is to be performed, particularly in low signal-to-noise ratio (SNR) conditions. Simple FFT approaches can introduce an artificial scalloping pattern in the power measurement, reducing the accuracy of the power measurement. By summing over multiple bins, this effect is reduced, but at the expense of reducing the receiver’s dynamic range. PLL approaches can have improved accuracy tracking the beacon frequency, but results in additional hardware and will have difficulty re-acquiring the signal in conditions of low SNR.
The software-defined beacon receiver approach described here is implemented by first using the Quinn-Fernandes (QNF) frequency estimation algorithm to estimate the frequency of the received beacon signal. The QNF is one of a variety of frequency estimation algorithms that starts by taking the FFT of the data, but produces a frequency estimate with greater resolution than the resolution of the FFT alone. This is accomplished by looking at the relative power levels of the peak bin, and one or more neighboring bins, and interpolating the frequency between bins. The QNF approach is further improved upon for beacon receiver applications by utilizing prior estimates to limit the search range of the beacon frequency (since beacon frequency drift is slow-varying in nature). In situations of low SNR, the modified QNF approach is capable of tracking the peak signal to within 3 dB of the noise floor and instantly reacquiring the signal when the SNR improves.
This unique approach has the advantage of increasing the accuracy of the frequency estimate, and hence, the power measurement of a beacon signal; increasing the robustness of the receiver in low SNR conditions; and reducing the restrictions on selecting the sampling frequency and number of samples, improving the operational capability of the beacon receiver to measure with a higher frequency (e.g., for observing atmospheric scintillations multiple times per second).
This work was done by James Nessel, Michael Zemba, and Jacquelynne Morse of Glenn Research Center. Inquiries concerning rights for the commercial use of this invention should be addressed to
Inquiries concerning rights for the commercial use of this invention should be addressed to
Refer to LEW-19222-1.