USAF/US NAVY 6G Fighter Programs - F/A-XX, F-X, NGAD, PCA, ASFS news

rooster said:
iverson said:
In_A_Dream said:
I don't think the military really needs to get surgical with AI controlled assets. Simply overwhelming an enemy force with expendable drones is enough to do the job.
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Indeed. Ukraine's Turkish-made Bayraktars seem to be little more sophisticated than cutting-edge hobbyist equipment. They have a "ludicrously" small payload. Yet they have been perhaps the most successful combat drones in history, while operating in the face of the much vaunted air defenses of the West's most sophisticated opponent. Actual, quadcopter hobbyist drones have proved decisive for artillery spotting and scouting for tank hunting teams. Some have even been used as ultralight bombers.

The value of these cheap platforms has derived not from the technology itself, essential though that is, but from the imaginative way in which they have been used to gain leverage on the real-world, here-and-now battlefield. The Ukrainians have skillfully matched the limited capabilities and payloads offered by the technology to the available range of targets, taking into account potential countermeasures.

The Ukrainians understand this technology--what it is, what it can do and what it is not and cannot do.
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Russia isn't much of an opponent. Hasn't been for over 3 decades. I would not make decisions about the air power of the USA based on russia. In under 30 years the USAF will have fielded 3 new fighters and Russia still struggles with one new idk what to call it... 4.5 gen aircraft.
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This. By 2027, Norway-Finland-Poland (all on Russia’s border) will have 150 F-35s compared to Russia’s contracted 75 Su-57s, assuming that they are delivered on time. US AirPower should be solely designed with China and the Pacific theater in mind.
 
I am pretty sure that this reluctance to get more Lightnings is only a way to get their rear lines solid.
 
iverson said:
shin_getter said:
For example, I expect the profiling of all human aviators (if skill differential is notable) and systems that enable real time identification via non-cooperative means. There'd be tactical "interactions" to collect this info and other things, and considerations in defeating/neutralizing each "human constraint" would be part of the combat model.
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One question: what is the "the profiling of all human aviators"? How is it done? What attributes, methods, and parameters do you include? How, for example, do you measure "skill" in order to differentiate it? What is "skill" in this context? What units, instruments, and protocols do you use when doing the measuring? Are we counting G-tolerance? eyesight aerobatic ability? ability to calculate fuel burn? navigational skill? Tactics? Strategy" Knowledge of rules of engagement/military law/international law? Good judgment? And, fi we are, how do we balance them against each other when arriving at a "profile"? Are the units and measurement methods appropriate to each common to all?
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The answer is: All of them. Every piece of data that can be collected will be thrown into a model and big data systems will be used to extract maximum value out of the information.

You first start without your own pilots, collect data on building predictive models on tactically relevant factors and observables, ideally parameters you can observe in the enemy while fighting. After observing things like minimum energy loss missile evasion or Complex maneuvers at high G or fast response to expected detection of friendly forces, opponent model gets built up, both over time and instantly updated to the entire tactical fleet. This information can be cross correlated with things like personnel databases, peace time data collection and such to enable potentially identification of individual pilots by external observation in real time.

But that would just a small side project in the identify contacts by means of data fusion. Sensor data is insufficient in a world of VLO inside swarms of decoys, instead vehicle behavior and relative positions will be fed into the model to improve predictions. A naive opponent following simple command and control logic would get his decoys, his high bandwidth remote controlled drones, his manned command and control aircraft identified by observation of behavior, and get tactics made to counter, from saturating command nodes, finding ideal locations to insert jamming assets, and finding coordination issues between command nodes, predictable and exploitable behavior to threats and so on. The Kosovo F-117 shootdown was the simplest of patterns, in the world of bigger data there is far more patterns to pick up.

A smart opponent would find means to deceive you, and fleet scale tactics grow in complexity as manned aircraft pretend to be drones and drones pretend to be manned. Side-band information like human sleep cycles, best guess on aircraft maintenance time requirements would be combined with battle damage information, models of opponent logistics capabilities and so on across the entire front to figure out optimal force employment: everything from wearing out enemy air fleet to setup a maximized attack at point of low availability to creating local superiority due to predictable scramble patterns given a day of week all can be worked out.

The details is not something you can know beforehand, you can just do you best to collect and plan, and stumble up exploitable information once a while. The details is warfighting itself, and both sides in a competitive fight will be doing everything to improve their understanding, modeling of the opponent while doing their best to deceive the opponent.

Trillions of data points will be collected, thousands of ideas and models explored, hundreds of software changes is to be expected throughout a campaign. Most of the data, ideas and models would be failures that does nothing useful, but only a few of them needs to be effective for significant military advantages, and with modern big data infrastructure, exploring and using all that data and ideas is cheaper than ever.

The art of war is not something you train before the war and execute by memory. The ability for AI systems to go beyond peak human abilities in tactics in a day of wall clock time with only a few mil of compute means that the art of war can be developed in real time with the particulars of a conflict pinned down right at the point in time.

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The air force making AI as lower bandwidth RC airplanes is a far cry from all integrating hyper-informational model that seeks to outthink opponent on all levels of conflict across all domains that would be the end game to AI technology. Robot airplanes is just a more reliable actuators to such a model.

This is my core critique of "AI", as practised today. It pretends to be something that it cannot rigorously define. No one has come up with a reasonable definition of "intelligence". And without that, how do you know what you have implemented?
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You don't need "intelligence", you just need behavior that leads to fulfillment of objectives. Design a scoring function on a model of reality and it reduces to a optimization problem that you can use a world of tools to compute.
 
shin_getter said:
The answer is: All of them. Every piece of data that can be collected will be thrown into a model and big data systems will be used to extract maximum value out of the information

You first ... collect data on building predictive models on tactically relevant factors and observables, ideally parameters you can observe in the enemy while fighting. ... opponent model gets built up, ... cross correlated with things like personnel databases, peace time data collection and such ...

But that would just a small side project in the identify contacts by means of data fusion.... <snip>

The details is not something you can know beforehand, you can just ... stumble up exploitable information once a while. ...

Trillions of data points will be collected, thousands of ideas and models explored, hundreds of software changes is to be expected throughout a campaign. ...

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The air force making AI as lower bandwidth RC airplanes is a far cry from all integrating hyper-informational model that seeks to outthink opponent on all levels of conflict across...

This is my core critique of "AI", as practised today. It pretends to be something that it cannot rigorously define. No one has come up with a reasonable definition of "intelligence". And without that, how do you know what you have implemented?
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You don't need "intelligence", you just need behavior that leads to fulfillment of objectives. Design a scoring function on a model of reality and it reduces to a optimization problem that you can use a world of tools to compute.
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So, we somehow "outthink [an] opponent" without "intelligence"? This is just the kind of loose talk that drives sloppy "AI" "solutions" to non-problems.

"Every piece of data that can be collected will be thrown into a model and big data systems will be used to extract maximum value out of the information"?

Seriously? "Data" is not "information". Collecting all of it without defining what you are looking for creates noise, not knowledge. For example, the number of nose hairs in an average pilot's left nostril and the same pilot's visual acuity are both data. Whether either or both or neither is information is something we cannot determine until we have defined the question that we are trying to answer and done some controlled experimentation. The same goes for all "observables": we've know since Francis Bacon that uncritical, empirical observation is not knowledge and does not answer scientific questions. Empirical evidence is a mixture of noise (lots) and signal (very little). Without well-considered and well-constructed filters, you have nothing.

So you can't just blithely refer to "tactically relevant factors" in passing. Until you have defined what, exactly, is relevant, tactically or otherwise, and tested your definition with controlled experiments, data--observables--are useless. The buzz words "AI", "model", "Big Data", "data fusion" are supposed to dazzle us with visions of super tech. But all they do is obscure the difference between information processing and random data gathering.

You imply that we cannot define requirements with adequate granularity because we cannot know the future, but must instead proceed from vague requirements "like ""data fusion"" in the hopes that more precise requirements will emerge eventually by pure chance: "The details is not something you can know beforehand, you can just ... stumble up exploitable information once a while." But it is because we cannot know the future that we formulate hypotheses, test them under controlled conditions, and then define specific requirements for dealing with the most likely future outcomes. Understanding precisely what happens now is our best guide to what may happen next--and the basis of science.

Perhaps a slightly more detailed example of the real-world that lies behind "AI" and "big-data" hype will help. I started in my current profession as a database programmer. Databases work because you start with a specific problem that the database is supposed to solve--the more specific the definition, the higher the likelihood of success. You then define a set of expected relationships between data points and set up tables, keys, indices, etc. accordingly. When ready, you test the results. In my first case, the subscribers got their issues on time, the publisher got its subscription fees, and I got my fee. Success! My model of the client's business worked. From what I have seen subsequently, vastly larger and more complex corporate databases are developed and work in exactly the same way.

Ignoring the original design, purpose, and structure of a databases undermines its utility and validity. By doin so, you essentially strip it of ithe controls and and logical relationships that make information out of data. Terms like "AI", "big data", "data mining", and "data fusion" obscure this reality to sell systems. Corporate suits can believe that they can gain low-cost , spontaneous "insights" simply by munging all their old databases together. Value for nothing, almost. Credit reporting companies, advertisers, and surveillance-state types in our governments love this approach because it is easy to understand (if you do not think to much) and seems to offer extra return on the investment they made in the original databases. Throw enough miscellaneous data together, stir, and wait for the goodness to emerge from the soup--like magic.

And magical thinking it is. The purpose and design of the collection, storage, and processing system determines the information value of the collected data. Combine them uncritically under the "throw-it-all -in" big-data model and you lose any possibility of drawing reliable conclusions. You take away the order and the result is just noise. Patterns will emerge from this chaos, just as the "big-data" experts claim--humans find patterns in the tile floors of public restrooms--but their will be no reason to think that the patterns are meaningful/useful/actionable and no way to test them. Acting upon a revelations revealed on the men's room floor is no the way to achieve greatness. (Think about this the next time a corporate leader talks about "data-driven decisions",)

My direct experience with actual "big-data" work is admittedly limited but also revealing. I joined a project that was sold on the basis of "AI". My job was to document the different parts of a large, complex integration for the client. One problem emerged: I could not figure out what the "AI", the "predictive analytics" software installed on client systems actually did. It did not seem to be connected to anything. It turned out that "AI" was a required part of the bid, but had nothing to do--it was, euphemistically speaking, a "future capability" that was included to keep non-technical suits happy, both in our company and in the client's. The "data-mining" also did not proceed per the marketing team's "big-data" pitch. The client's many databases were not "combined" (munged). Instead, a team of database analysts with a decade plus of experience in the client's line of business systematically copied and dismantled the original databases, rigorously classified the data, and then transferred the contents field-by-field to a new database that was purpose-designed for use with analytic algorithms designed specifically for the customer's business problem. A classic database solution that met the client's real requirements., while ignoring the meaningless "AI" in the original request for proposals.

There are no shortcuts for achieving the kind of performance that you want from your robot airplanes. Achieving it (if it is achievable) will be an enormous and, yes, dangerous undertaking, not because of the rise of Skynet but because of the potential costs and consequences that result from errors in large, complex systems. You cannot count on technical advance to somehow spare you the effort of defining requirements, because that effort is technical advance.
 
AI as it stands now doesn’t think or necessarily make decisions well. What it can do, with unnerving accuracy, is find patterns in vast data sets in near real time. One of my favorite examples is Amazon software literally predicting pregnancy by shopping patterns, before the person involved necessarily knows.

Random is just a word we use to describe situations where humans can’t find a pattern. AI isn’t truly intelligent or sentient but it does have the capability to detect patterns in vast, complicated datasets and react accordingly or else suggest a course of action.
 
Josh_TN said:
AI as it stands now doesn’t think or necessarily make decisions well. What it can do, with unnerving accuracy, is find patterns in vast data sets in near real time. One of my favorite examples is Amazon software literally predicting pregnancy by shopping patterns, before the person involved necessarily knows.
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IIRC it was Target, not Amazon, and it was before the teen's father knew. She did now.

As for the relevance of findings by big data, one shining example is about the root cause of death in humans. Death is found to be correlated with 100% accuracy to ... birth.
100% correlation is hard to argue with!
 
Hello everyone,

I am an intern at a consulting company mainly based in France, and I am searching on all kind of NGAD program in the world but I am looking for many more details about the program that maybe you can all here have.

Actually, I am trying to establish all of the complet ecosystem about the NGAD: which aircrafts will fight with the F-X? And even more, Which will be all the actors in the fight with the F-X? NGAD does it include multi-environment management such as maritime, spatial or even land? Namely, does the program include that the fighter and the UAV will be directly linked with soldier on the land or in ground base?

I have done lots of research but maybe you guys will learn me some new things, my actual vision of the NGAD program seems incomplete



Thank you for your consideration and sorry for my English.


 
Thats kinda what I was thinking, especially since the exact requirements for them will probably change fairly often
 
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It never seemed realistic to me to iterate through manned aircraft that quickly. By the same token UAV development already proceeds dramatically faster; the US has already gone through an entire generation of UAVs in two decades and it’s second generation is already considered obsolescent. I can easily see the UAV components of NGAD being refreshed every five years with digital design and 3D printing looking at projects like Speedracer and Gray Wolf.
 

An unknown number of companies are still competing to build the sixth-generation fighter... ​

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Translation: More than the 3 well known companies of always. Which leaves General Atomics, Scaled Composites, Kratos and Sierra Technical as the possible bidders... No way.

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The USG could split the manned/unmanned elements between LMCO, NGC and Boeing. I could be wrong with this statement but I will go out on an assumed limb; LMCO, manned USAF 6th gen fighter, Boeing, manned USN 6th gen fighter, and NGC for the sophisticated unmanned platform(s), thoughts and comments always welcome.
 
It is not pre-determined and a lot is dependent on who presents what and how competitive that is. McDonnell Douglas did not win the contract to build the F-15 Eagle replacement. LM produced neither the F-16 (pre-GD acquisition), nor the F-15 or F-14 and is now the only 5th gen game in town in the US. So a lot will depend on who has a lead when it comes to the technologies and capabilities the USAF and USN are looking for in a future platform and associated family of systems. We're obviously great at looking at recent history and applying a similar logic into the future but things can change dramatically and companies often change and prioritize different capabilities. I found it interesting that the Skunk Works promoted someone with a recent ISR and unmanned? background to replace their outgoing boss who had been pivotal for their fighter portfolio.
 
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www.19fortyfive.com

NGAD Update: F-22 Raptor Will Test 6th Generation Stealth Technology

The Air Force has already gone to Capitol Hill to ask lawmakers for about $1.7 billion to fund the NGAD program in its new budget.
www.19fortyfive.com www.19fortyfive.com
"It would appear that technological development is now flowing both ways. The F-22 will be used as a test platform for the NGAD technologies, and where appropriate, some of the technologies developed under the program could then be employed with the Raptor. This could aid in the development of the NGAD aircraft but also serve to help maintain the F-22’s edge as other nations seek to develop fifth- and even sixth-generation fighter aircraft."

www.thedrive.com

Air Force's Next Generation Air Dominance 'Fighter' Program Enters New Stage

The goal now is to turn the Next Generation Air Dominance program into a real capability by the end of the decade.
www.thedrive.com www.thedrive.com
 
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Placeholder NGAD concept via TWZ (or sneak peek into the real thing?):
cmmt-swarm.jpg

 
If this video is to be taken at face value, LMs' own opinion on F-35 stealth seems to be not very high.
Thus I wouldn't place too much trust in it.
 
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It seems likely to me that one of the normal big contractors gets to be the prime for the manned platform, but there seems like lots of opportunities for smaller companies to build the unmanned components. It looks likely that there will be at least three pieces to that - unmanned disposable, unmanned attritable, and unmanned..."hope we get this expensive piece of machinery back". On top of that it looks like there might be room for UAVs with specialized roles and envelopes, like high altitude ISR/communications (I would have thought "RQ-180" filled that niche but perhaps they are in too high demand and something smaller and more "tactical" is desired). I could see 2-3 different contractors providing the non-manned elements of NGAD given the diversity of need and the number of producers of UAVs who have existing products that slot in neatly to those diverse roles.
 
elmer said:
The F-22 will be used as a test platform for the NGAD technologies, and where appropriate, some of the technologies developed under the program could then be employed with the Raptor.
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I have a suspicion the "one year" NGAD X plane was in fact a modified F-22 ........ maybe X-44, maybe. Certainly would make sense.
 
djfawcett said:
I have a suspicion the "one year" NGAD X plane was in fact a modified F-22
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What if the USAF had secretly dug out of secure storage some of the F-22 production jigs and tooling and used it to be build a new F-22 with upgrades?
 
It’s hard to imagine how such an aircraft would de risk the program or that any of the same production methods would be applicable/useful.
 
djfawcett said:
elmer said:
The F-22 will be used as a test platform for the NGAD technologies, and where appropriate, some of the technologies developed under the program could then be employed with the Raptor.
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I have a suspicion the "one year" NGAD X plane was in fact a modified F-22 ........ maybe X-44, maybe. Certainly would make sense.
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Doubtful
 
NMaude said:
djfawcett said:
I have a suspicion the "one year" NGAD X plane was in fact a modified F-22
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What if the USAF had secretly dug out of secure storage some of the F-22 production jigs and tooling and used it to be build a new F-22 with upgrades?
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In essence restarting a broken-down production line for ONE plane would be... <British accent>Rather expensive and perhaps a bit wasteful.</British accent>
 

How Boeing Is Positioning Itself For Advanced Fighter Competitions​

Brian Everstine
July 20, 2022

[...]Boeing is presumably in the mix for the U.S. Air Force’s Next Generation Air Dominance (NGAD) platform, which Air Force Secretary Frank Kendall told lawmakers earlier this year has entered the engineering and manufacturing development phase. But neither Kendall nor a series of Boeing officials would elaborate on anything NGAD-related when asked at Farnborough. The U.S. Navy is similarly planning its next-generation fighter.


“Fighters are in our DNA, right,” says Rik Geiersbach, Boeing Defense’s vice president for strategy. “So there was a competition 20-plus years ago for F-35. We did not stop investing in future fighter capabilities then, we don’t stop investing in future capabilities now. So the fact that there are needs that are relative to future capabilities, you can rest assured that we are right in the middle of all of that.”
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How Boeing Is Positioning Itself For Advanced Fighter Competitions | Aviation Week Network

Phantom Works continues to invest in the future of combat aircraft as the U.S. Air Force and Navy plan for next-generation fighters.
aviationweek.com aviationweek.com
 
iverson said:
All of these futuristic unmanned aircraft will, in fact, be "flown from the ground", whether or not they have data links and ground-based pilots. They differ from the older "Remotely Piloted Vehicles" only in that the operators are remote in time as well as space.
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B R A V O ! ! !
 
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Speaking during a quarterly earnings call with investment analysts, Kathy Warden touted Northrop’s work building a new Air Force stealth bomber as a reason why the company should be considered a contender.

“As we think about sixth-generation aircraft, we are in the process of building the first of those, the B-21, and that's given us some fantastic experience and lessons that we believe we can apply to other sixth-generation aircraft and so we're positioned as a competitor,” Warden said. “I think our government desires to have a broad industrial base able to prime these large opportunities as possible, and we have been clear that we are investing and building our own capabilities and capacities to be able to be a contender.”
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www.defenseone.com

Northrop Grumman CEO: We Can Build a Next-Generation Fighter

Kathy Warden said the company’s B-21 stealth bomber positions it well to compete for the Next Generation Air Dominance warplane.
www.defenseone.com www.defenseone.com
 
The AUKUS agreement was initially focused on sharing technology related to nuclear-powered submarines, but its scope has expanded in the months since. Australian ambassador to the U.S. Arthur Sinodinos noted in November that it will also include “enhanced” air and space cooperation.

“There’s so much more that’s being thought about,” Metrolis confirmed, “especially in air and space: the E-7 [Wedgetail], fifth- and sixth-gen fighters. Sixth-generation might become an AUKUS pillar.”

How exactly that might manifest remains to be seen. While the U.K. is developing Tempest and the U.S. is pursuing NGAD, Australia has yet to publicly involve itself with a sixth-generation program.

As those future decisions are made, Metrolis said there will be economic and industrial base considerations. But even more so will be the question of interoperability.

“We’re very interoperable with the U.K., more than any other nation,” Metrolis said. “
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www.airforcemag.com

US, UK Will Have ‘Avenue' to Share Best Practices for Sixth-Gen Fighter Development - Air Force Magazine

As the US and Great Britain pursue different sixth-gen fighters, they'll still find ways to collaborate, the US air attaché in London said.
www.airforcemag.com www.airforcemag.com
 

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