WSPRnet Passive Radar and the Search for Flight MH370
By Eric Hendrickson
Recently, I’ve been following some groundbreaking research suggesting that WSPRnet, the global network used by hams to log weak signal propagation reports, might have untapped potential as a passive radar tool. This revelation has taken on a particularly poignant dimension in the context of the ongoing search for Malaysia Airlines flight MH370, one of modern aviation’s most perplexing enigmas. As of February 2025, the search for MH370 has resumed, partly due to efforts of the amateur radio community and analysis of historical propagation data.
WSPRnet: More Than a Hobbyist’s Tool
When MH370 disappeared in 2014, the world was left with an almost surreal void—a mystery that challenged conventional wisdom about aircraft tracking and search-and-rescue operations. How could a Boeing 777 simply disappear without a trace? In the absence of clear, real-time radar data, investigators had to rely on satellite signals and a range of other clues that only hinted at what might have happened. In that era of uncertainty, it’s both humbling and inspiring to consider that something as subtle as the transmission of low-power radio signals across continents could one day help shed light on this enduring puzzle.
WSPR, which stands for “Weak Signal Propagation Reporter,” is a mode of digital communication used by amateur radio operators around the globe. WSPRnet collects data on these signals—their signal-to-noise ratios, frequency shifts, and precise time stamps—creating a continuously growing archive of information that offers unique insights into the behavior of radio waves.
A Seemingly Incredible Proposal
Richard Godfrey, an aerospace engineer and member of the Independent Group—a collective of scientists and researchers dedicated to solving the MH370 mystery—has been at the forefront of utilizing WSPRnet data to track the flight path of Malaysia Airlines Flight MH370. In May 2021, Godfrey proposed that anomalies in WSPR signals could be analyzed to detect and track aircraft movements over long distances. By November 2021, he reported that his analysis indicated the aircraft flew in circles for approximately 22 minutes in an area 150 nautical miles from the coast of Sumatra before vanishing.
Collaborating with Dr. Hannes Coetzee and Professor Simon Maskell from the University of Liverpool, Godfrey co-authored a technical paper titled How does WSPR detect Aircraft over Long Distances? This work delves into the potential of the WSPRnet system for long-distance aircraft tracking.
However, it is important to note that the application of WSPRnet data in tracking MH370 has been met with some skepticism. Critics argue that the weak signal anomalies detected by WSPR are too faint and inconsistent to reliably trace an aircraft’s path. For instance, Victor Iannello, also a member of the Independent Group, contends that the signals scattered by aircraft are orders of magnitude too weak to be detected and decoded for such purposes. Similarly, Nobel laureate and WSPR creator Joseph Hooton Taylor Jr. dismissed the idea, stating, “It’s crazy to think that historical WSPR data could be used to track the course of ill-fated flight MH370.”
Despite these differing viewpoints, the analysis of WSPRnet data remains a topic of interest in the ongoing efforts to uncover the fate of MH370.
The Passive Radar Revolution
The concept of using WSPRnet as a passive radar tool is both innovative and challenging. Traditional radar systems operate by emitting pulses of RF energy and measuring the echoes that return after bouncing off objects. Passive radar, by contrast, makes use of existing transmissions. Instead of sending out its own signals, a passive system listens to the ongoing “chatter” of the radio spectrum, searching for anomalies in the data. It’s these anomalies—minute deviations from what is expected—that might one day provide a glimpse into events that, until now, have remained shrouded in mystery.
At the technical heart of this approach is the phenomenon of multipath propagation. When a radio signal is transmitted, in addition to the signal taking a direct route to the receiver, signals also encounter obstacles along the way and reflect off certain surfaces such as the ionosphere or terrestrial features, and ultimately reaches a receiver via multiple paths. Under normal circumstances, the interference patterns created by these different paths are predictable and form a sort of “signature” unique to each transmission path. However, when an object as large and reflective as a commercial aircraft enters the picture, it disrupts these patterns. The aircraft may absorb or reflect portions of the signal, creating small, yet detectable, deviations or doppler shifts in the expected signal.
Digging into the Technical Details
In recent years, improvements in digital signal processing and machine learning have opened new possibilities for extracting meaningful information from vast datasets like those provided by WSPRnet. Sophisticated algorithms are now able to sift through terabytes of historical data, isolating moments when the normal signature of a radio signal appears to have been disturbed. These disruptions, subtle as they may be, can potentially be linked to the passage of an object—like MH370—through the transmission’s path. While the idea might sound like science fiction, it’s grounded in rigorous scientific analysis and represents a fascinating convergence of hobbyist passion and high-tech research.
The challenge, however, lies in differentiating genuine aircraft signatures from the inherent noise that is part and parcel of the radio spectrum. As hams, we all know that radio signals are influenced by a myriad of factors: Atmospheric conditions, solar flares, local interference, and even the time of day can all leave their imprint on the data. The science of this method, therefore, lies in the ability to identify a true anomaly amidst a cacophony of natural variations. Techniques like time–frequency analysis and cross-correlation functions have been employed in recent studies, allowing researchers to compare expected propagation behaviors with the actual recorded data. The objective is to isolate those fleeting moments when the interference pattern shifts in a manner that could indicate an aircraft’s presence.
Overcoming the Noise: The Quest for Clarity
One of the more fascinating technical aspects is the need for precise calibration across a globally distributed network of receivers. Variations in receiver sensitivity, differences in antenna performance, and local environmental factors all contribute to a level of variability that must be accounted for in any analysis. This calibration process is crucial to ensure that the data collected from disparate locations can be reliably compared. It’s a challenge that underscores the meticulous nature of this research—a challenge that is as much about engineering precision as it is about theoretical insight.
Integrating high-resolution environmental data with WSPRnet logs adds another layer of complexity and precision. By correlating the radio data with atmospheric models, researchers can better understand the impact of phenomena like solar activity or weather patterns on signal propagation. This integrated approach not only refines the models but also enhances our ability to distinguish between benign variations and those that might indicate an interference event caused by an aircraft.
The MH370 Puzzle and the Promise of Passive Radar
The potential implications of successfully using WSPRnet as a passive radar tool extend far beyond the mystery of MH370. Traditional radar systems, while highly effective, are often limited by geographical constraints, especially over vast oceanic regions where coverage can be sparse. A passive radar system, leveraging the ubiquitous signals already present in our environment, could provide a crucial supplement to existing surveillance methods. Such a system might one day play a pivotal role in search-and-rescue operations, offering real-time tracking capabilities in areas where active radar installations are impractical or prohibitively expensive
For me, the idea that my modest contributions to WSPRnet could be part of a future technology that enhances aviation safety is both humbling and inspiring. It’s a potent reminder that sometimes the smallest actions—in this case, transmitting a weak signal from a simple setup—can be part of a much larger tapestry of innovation. The possibility that we might someday use passive radar techniques to track aircraft in real time, or even to retrospectively piece together the path of MH370, speaks to the profound potential of collaborative, citizen-driven science.
A Journey of Discovery
Of course, there is a need for caution and rigorous validation before any definitive claims can be made. The scientific process demands that hypotheses be tested repeatedly, and in this field, that means cross-verifying any potential aircraft signature against known benchmarks. Researchers are already exploring methods to test these models against flights with well-documented trajectories, fine-tuning their algorithms to account for the inherent uncertainties in radio signal propagation.
The search for MH370 is a story filled with sorrow and unanswered questions, and while the use of WSPRnet data does not promise immediate solutions, it represents a beacon of hope—a new avenue to explore in a mystery that has long confounded experts and left anxious families longing for answers. By meticulously reanalyzing historical data from the time of the disappearance, it may be possible to uncover subtle clues that have been overlooked by traditional methods. This approach isn’t about replacing established techniques but about adding an additional layer of investigation that could one day help piece together the puzzle.
Looking Ahead: The Future of Passive Radar
The future of passive radar using WSPRnet data is both exciting and uncertain. Significant hurdles remain—not least of which is the need for a more comprehensive understanding of the interplay between radio signals and atmospheric phenomena. The continuous improvement of computational models and the integration of diverse data sources will be critical to advancing this field. Yet, the progress made thus far serves as a powerful reminder that even the most humble of tools can have far-reaching implications. You can contribute to the immense pool of public data available simply by using WSPRnet in your own shack.
