Weak Signal Propagation Reporter (WSPR): Implications for Anomalies Research

Douglas G. Richards

Atlantic University, Virginia Beach, VA, USA

Introduction: The Weak Signal Propagation Reporter (WSPR) is a signal processing algorithm for extremely weak radio signals. Much anomalies research also tries to detect extremely weak signals: psi, global consciousness, geomagnetic field effects, and other anomalous biological/psychological phenomena. Studies using WSPR provide a useful methodological comparison for other studies of weak signals. WSPR may also be applied directly to studies of anomalies involving the effects of the geomagnetic field and ionospheric resonances on biological systems. WSPR uses free software available on the Internet, and WSPRnet is a global, free shared database of WSPR data.

Discussion: The intended application of WSPR is to explore the effects of phenomena like geomagnetic field variability, time of day, sunspots, time of year, sidereal time, etc. on radio propagation. These same variables may affect human behavior and rhythms including psi and health (Alabdulgader et al., 2018; Krippner & Persinger, 1996; Spottiswoode, 1997). Direct measurement of geomagnetic/solar phenomena requires expensive equipment, is generally conducted at only a few stations around the world, and is not usually available at a fine temporal or spatial resolution. In contrast, WSPR has a network of hundreds of transmitters and receivers around the world; for receiving, anyone can contribute to the database; for transmitting, an amateur radio license is required. The database itself is completely open and there are websites with tools for statistical analysis.

One of the challenges in weak signal/high noise research is that uncontrollable noise plays a major role (in contrast to many fields of laboratory research where the noise can be controlled). WSPR was developed by physicist Joe Taylor at Princeton University to address this problem in radio communication. WSPR measures the signal-to-noise ratio (SNR) of extremely weak signals, with a threshold 31 dB below the noise floor (in other words, signals that normally would not be detected at all). For example, using only 0.1 watt in the 40 meter ham radio band, I am heard clearly in Antarctica, over 14000 km away.

I will use a rebuttal to one of the criticisms of psi research as an example of the application of this principle. A frequent skeptical argument against the reality of psi is that it does not obey the “inverse square law,” that the magnitude of a force declines with the square of the distance (e.g., Reber & Alcock, 2019). It is true that some psi effects seem to be unrelated to distance, at least over terrestrial distances. However, the skeptical argument is completely spurious because in communication, it is the signal-to-noise ratio, not the magnitude of the signal, which is relevant.

The SNR of my signal in Antarctica is similar to that in California, Texas, England, and nearby Norfolk – just like psi, there is no apparent dependence on distance. WSPR can’t be used directly in psi research, since we do not even know if psi is a signal, or what the noise level may be. But this illustrates a way of thinking about weak signal research.

WSPR can be applied directly to measurements in other areas of anomalies research. In particular, it can measure variables likely to be relevant in the study of the effects of solar weather and geomagnetic fields on biology and psychology. Alabdulgader et al. (2018) and McCraty et al. (2012) have demonstrated a coupling between the human nervous system and resonating geomagnetic frequencies. They have used a small network of measurement sites, separated by thousands of miles and typically with a time resolution of at best 3 hours. These can provide a broad picture, but WSPR can explore correlates of the same variables on a much finer temporal and spatial scale. For example, propagation changes during developing geomagnetic storms can be measured at 2-minute intervals by hundreds of worldwide stations, with results posted immediately to the Internet.

Conclusion: WSPR offers methodological insights for dealing with weak signal/high noise environments, and potential practical measurement capabilities for anomalies research. WSPR is an outstanding example of completely open research participation and shared data.

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Published on May 23, 2022