Unidentified anomalous phenomena: Hot spots and the quest for better UFO data

Regularly linked to alien-occupied flying saucers that have stopovers on Earth from the outer reaches of deep space is an equally puzzling enigma: Unidentified anomalous phenomena, or UAP, a new term that encompasses objects that can't immediately be identified that are detected in the sky, under water or in space or that appear to travel between these domains.

Specialized sensors are now being dispatched into the field. This gear is built to sight UAP and decipher what's behind frequent sightings in certain hot spots of activity. For years now, the UAP mystery has blossomed, driven in-part by military pilots that have recalled their related encounters. Congressional hearings, specially set up military organizations, even NASA itself — all have been engaged in their own close-encounters with UAP. So far, a consistent cry is "more data." 

Even SpaceX chief rocketeer, Elon Musk, admits he is hounded by those seeking the answer to the 'are we alone' query. "Are there aliens? Or is it … are we alone? People often ask me if I've seen any evidence of aliens. I unfortunately have seen no evidence of aliens yet. We are the aliens as far as I can tell. And I think if anyone would know, it would probably be me, and I have not seen any evidence of aliens," Musk recently said. 

To be in the know, and for many anxious to throw light on UAP, it's all about reliable, truth-revealing, and scientifically rigorous data collection. 

Related: NASA UFO report finds no evidence of 'extraterrestrial origin' for UAP sightings

Progress and improvements

There have been several attempts since the 1950s to use specialized sensors to identify UAP, said Robert Powell, Executive Board Member of the Scientific Coalition for UAP Studies (SCU). "The problem has always been the unlikelihood of having a UAP show up where your high quality sensors happen to be located."

Today, a number of modern groups have developed UAP detection systems, Powell said. "Definite progress and improvements have been made."

While the ability to build and deploy these types of systems is farther ahead today than ever before, said Powell, "none of these current programs have either quantity of systems or a quality standardized system that would allow for large numbers to be utilized in a controlled fashion."

Powell believes a successful UAP detection program will require a sizable budget to build, distribute, and maintain 1,500-plus UAP sensor systems, "but will also need to be able to hire staffing for the development and maintenance of such systems."

What's a cha-ching calculation ringing out from the cash register? In the tens of millions of dollars, Powell estimates.

Multimodal census

Taking a scientific stab at untangling the UAP conundrum is the Galileo Project, an effort led by Harvard astrophysicist Avi Loeb. 

This initiative has built an integrated software and instrumentation system designed to conduct a multimodal census of aerial phenomena and to recognize anomalies. Loeb believes that UAP present a long-standing mystery that can and should be investigated by the tools of contemporary science.

Loeb told Space.com that testing of the detection equipment is underway at a Harvard Observatory site and that the Galileo Project would be assembling a second observatory in Colorado.

"We are starting to collect data with our Harvard UAP Observatory and aim to analyze it with machine learning software," said Loeb. 

The goal is to automate the identification process and check whether objects are natural (birds, bugs), human-made (balloons, drones, airplanes), Loeb said, "or something from beyond Earth."

Wanted: consistency

Taking a fresh and novel look at the UAP detection scene is Alex Hollings, editor-in-chief of Sandboxx News. He notes that the Defense Department has used a wide variety of sensors to detect UAP in different circumstances, including electro-optical (video), infrared, and radar.

However, there doesn't seem to be a great deal of consistency, Hollings said, regarding detection across sensors. "That is to say that in some incidents, anomalous objects may be detected for instance by radar, but then not in others."

One element of the sensor conversation that's gone "under-discussed" in Hollings view, is the variety of radar arrays and frequencies that have been leveraged in reported UAP incidents. 

"There have been cases where the powerful shipboard radar systems leveraged by Aegis destroyers do detect an anomaly, while the fire-control radars aboard scrambled Super Hornet aircraft don't. That's sometimes seen as an element of added mystery, but today's tactical stealth aircraft can also produce different results depending on radar frequency. But beyond finding the right radar frequency, we also need to find a way to sift through all of the data we have more effectively." Hollings said.

Mountain of data

In the big picture radar scene just here in the U.S. consider all the territory the military keeps tabs on every day. It comes out to around 29 million square miles (75 million square km).

"So, in order to sift through all the chatter, the military establishes filters, akin to when a person searches for a used car online, effectively saying: 'Only show me things that meet this criterion.' It takes a mountain of data and turns it into a pretty large pile, and then people are stuck pouring over that pile to look for threats or issues," said Hollings.

The same is true for integrated air defense systems and more localized radar arrays. Take for instance the MIM-104 Patriot system that works in a similar fashion, Hollings points out, only flagging returns that might represent inbound threats.

"But all these arrays do detect a ton of other stuff, from flocks of birds to dense clouds and everything in-between," observed Hollings.

Leveraging artificial intelligence

"Going through all of that radar data is nearly impossible for human eyes, but leveraging artificial intelligence to sift through all the static may yield promising results," Hollings said. 

Similarly, AI might eventually be able to detect stealth aircraft using existing radar arrays by just filtering the chatter — perhaps a capability useful to detect UAP to cull out a trend or pattern associated with them.

"If UAP researchers can identify some commonalities between anomalous radar returns, those can be used to train AI to hunt them down elsewhere," said Hollings.

Propulsion detection

Then there's use of infrared or thermal detection to identify and learn more about UAP.

"Heat detection can obviously tell us a lot about propulsion, that is, if we're talking about something that has propulsion. If so, whether or not UAP makes use of a combustion-based model via exhaust. And if there isn't exhaust ... well then we're talking about something that either doesn't use propulsion, like a natural phenomena, perhaps, or something that uses a form of propulsion that we're entirely unfamiliar with," said Hollings. 

But beyond propulsion, Hollings said he's interested to see how infrared sensors can capture UAP to determine whether or not these things could potentially be some sort of laser-induced plasma filament holograms. The U.S. Navy just so happens to hold a patent for such a technology.

Holograms and Occam's Razor

"Such a hologram would be capable of incredible speeds and maneuvers that seem to defy physics, may not produce a radar return, and could potentially be very convincing," said Hollings. "Over water, I contend that it may be possible to project such a hologram from a surfaced submarine ... but that's a tall order," he said.

Projecting such a hologram over land would be an even taller order, Hollings added. But admittedly, Occam's Razor rears its head. That's a scientific and philosophical rule calling first for the simplest, known quantities of competing theories over more complex explanations of unknown phenomena.

This means invoking Occam's Razor over alien visitors in the absence of any other data, Hollings said.

Military activity

Earlier this year, jumping into the UAP fray was RAND, a think tank to help perk up policy and decision-making through research and analysis. Their report was titled, Not the X-Files - Mapping Public Reports of Unidentified Aerial Phenomena Across America.

RAND specialists looked into where are people likely to report sightings of UAPs in the United States. Also, what factors predict where people are more or less likely to report UAP sightings?

Results from the RAND analysis yielded advice for government officials, pointing to outreach with civilians located near military operations area, and the need for improvements in data collection.

"We hypothesize that many civilians may not be aware that they are located near areas where military operations occur," the RAND study points out. UAP reports are significantly associated with areas of military activity. If some of these UAP reports are in fact authorized aircraft, the report continues, "then communicating that such activities are being conducted nearby could reduce the likelihood that the public will report these aircraft as UAPs." 

Public reporting

Furthermore, the RAND appraisal of the situation calls for design of a detailed and robust system for public reporting of UAP sightings. Such a system — perhaps managed by government agencies or non-government groups — would be useful in minimizing hoaxes and reports of misidentified objects. Indeed, public reporting of anomalous phenomena, the report adds, could be an asset for government authorities to identify potential threats in U.S. airspace.

"Greater transparency in how sightings are collected, investigated, and used may also help mitigate the conspiracy theories that have long surrounded aerial phenomena," the RAND study concludes.

All in all, there is a palpable uptick of action-item angst to get to the bottom of UAP identification. And that equates to digging in deep with data contends Sandboxx News editor Hollings.

"I think the only way we can find answers for UAP is by taking a systematic approach to identifying patterns in the data, he concludes. "If we can find just one commonality across multiple occurrences, it gives us a data set to search elsewhere at best … or at worst, may be able to point us toward new detection methods."