Are Traditional Armored Formations Becoming Obsolete in the Drone Era?

1. Precision Standoff Engagement
   Loitering munitions—often called “kamikaze drones”—will increasingly serve as organic, precision-strike assets for platoons and companies. Mounted on light vehicles or carried in trucks, these small UAVs can be launched minutes before contact, hover to identify high-value targets (tanks, APCs, logistics convoys) via electro-optical or infrared seekers, and then dive at armor weak points. Their loiter time and networked targeting mean that even armored formations will face the threat of sensors and warheads that can track, select, and hit them from outside the effective range of their own guns.
2. Swarm Saturation Attacks
   Looking ahead, nations will deploy large “swarms” of cheap, expendable drones working in concert to overwhelm vehicle defenses. Hundreds of small quad- or fixed-wing drones, each carrying fragmentation or shaped-charge payloads, can approach from multiple azimuths. While APS (Active Protection Systems) on modern tanks may destroy a few inbound threats, a well-coordinated swarm can saturate those systems—forcing vehicles to maneuver defensively, break formation, or risk penetration. Swarms will also be used to blind and confuse vehicle-mounted sensors, clearing the way for heavier drones or missile strikes.
3. Combined-Arms Integration & AI Autonomy
   Anti-vehicle drones will not operate in isolation but as integral elements of networked fires. Forward scouts—whether manned or unmanned—will “paint” enemy columns for drone loiterers, which can then autonomously choose which vehicles to strike based on pre-programmed target profiles. Machine-learning algorithms will allow drones to recognize specific vehicle silhouettes (e.g., by turret shape or thermal signature) and even re-assign targets in flight if higher-priority assets appear. Coordinated with artillery drones and recon platforms, these drones will give commanders a fast, responsive, and scalable anti-armor capability.
4. Mitigation, Counter-Swarm & Future Dynamics
   As lethal as anti-vehicle drones will be, armies will also field dedicated counter-UAS systems—short-range air defenses, electronic warfare pods to jam datalinks, and interceptor drones programmed to chase down loiterers. Vehicle designers will enhance low-observable coatings and introduce infrared-suppressing exhausts. Still, the era of hiding behind thick steel is ending: future survivability will hinge on mobility, dispersion, signature management, and layered active defenses. In this new domain, even light mechanized units will need organic drone wings to both strike and defend against the next wave of anti-vehicle UAV threats.

1. Dynamic Tasking & Reallocation:
   • AI algorithms onboard each drone will assess target priority—identifying high-value assets (e.g., command vehicles, artillery tractors) by their unique thermal and visual signatures.
   • Should higher-value targets emerge, drones can reassign themselves in mid-flight, ensuring the system concentrates its fire where it matters most.
2. Swarm Coordination & Collision Avoidance:
   • Sophisticated AI enables drones to fly collaboratively in dense formations, deconflicting flight paths and optimizing attack patterns.
   • Algorithms distribute drones across multiple engagement axes, maximizing saturation while preventing mid-air collisions—an exponentially complex problem as swarm size grows.
3. Adversarial Evasion & Deception:
   • Equipped with onboard machine-learning models, drones will recognize common anti-drone defenses (radar frequencies, jamming signatures, interceptor trajectories) and autonomously alter their flight profiles—diving through valleys, hugging terrain, or temporarily powering down emissions to slip past EW nets.
   • Some AI-enabled swarms may even deploy decoy drones programmed to mimic real threats, forcing defenders to burn precious interceptors.

• Jamming & Spoofing Arms Race: As defenders deploy EW pods to jam GPS or datalinks, attackers will field AI that dynamically hops frequencies, identifies and exploits spectral “holes,” or switches to inertial guidance with minimal signal reliance.
• ML Adversarial Attacks: Attackers can train their drone vision systems on “adversarial examples”—camouflage patterns or visual perturbations that cause defender radars or optical trackers to misclassify or ignore incoming UAVs.
• Rapid Learning & Adaptation: In-theater data collection allows AI models to be continually updated within hours, teaching drones to defeat the latest counter-UAS tactics. Meanwhile, defenders struggle to retrain their systems as quickly under contested conditions.

Option 1: Wheeled APC/IFV with Large-Caliber Cannon for Infantry Support​

Option 2: Surplus APCs Converted to Dedicated Counter-Drone Launchers or EW Vehicles​

Which Option Is Better?​

Miragedriver said:

Option 1: Wheeled APC/IFV with Large-Caliber Cannon for Infantry Support​

Concept:

Use 8×8 or 6×6 vehicles (e.g., Stryker, Patria AMV, Boxer, BTR80/90) up-gunned with a 30–40 mm cannon (or even a low-recoil 57 mm) capable of rapid airburst or programmable airburst ammunition.

Keep light armor to maintain high road and cross-country speed, easy strategic deployability, and low unit cost.

Advantages:

Area-Air Defense: Airburst rounds create an aerial fragmentation curtain—effective against small, slow-moving drones at close range (up to 2 km).

Volume of Fire: A high-rate cannon can engage multiple drones in quick succession, disrupting swarm attacks.

Multi-Role Utility: When not fighting drones, the same platform provides mechanized infantry support, convoy escort, and light anti-armor capability.

Mass and Redundancy: Lower per-vehicle cost means you can field more vehicles, diluting the risk if some are lost to enemy fire.

Hurdles/Considerations:

Sensor Package: Must be paired with an electro-optical/IR turret or lightweight AESA radar to cue the gun system.

Ammunition Logistics: Airburst shells are more expensive than standard rounds—requires mixed-load doctrine.

Option 2: Surplus APCs Converted to Dedicated Counter-Drone Launchers or EW Vehicles​

Concept:

Repurpose surplus or common APC hulls (M-113s, etc.) to carry pod-mounted anti-drone missiles (e.g., loitering interceptors) or scalable EW suites (RF jammers, directed-energy prototypes).

Vehicles operate in pairs or small teams alongside infantry and other combat systems.

Advantages:

Modular Payloads: Quick-change mission modules allow the same vehicle to act as a jammer, interceptor launcher, or sensor node.

Distributed EW / Kinetic Layer: A network of these vehicles blankets the battlefield with electronic and missile defenses, forcing swarms to contend with multiple denial and shoot-down zones.

Scalability & Cost-Control: Basic APC chassis are cheap compared to purpose-built air defense vehicles; payloads can be upgraded iteratively.

Flexibility: Can accompany mechanized units, protect logistics, or be staged as rear-area “drone bastions.”

Hurdles/Considerations:

Power & Cooling: High-power EW systems and directed-energy weapons demand robust onboard power generation and thermal management.

Spectrum Management: Friendly jamming must be centrally coordinated to avoid fratricide of friendly unmanned assets or communications.

Which Option Is Better?​

This distributed, affordable architecture leverages common, easily maintained hulls and allows militaries to scale their drone-counter capabilities without the prohibitive costs of heavy tracked vehicles or advanced fixed air-defense platforms. It also dovetails with modern combined-arms tactics—keeping infantry, armor, and UAVs mutually supportive in the face of AI-driven aerial threats. Now all we have to worry about is an EMP attack.

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FriedRiceNSpice said:

How much of that was AI generated?

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Breadbox said:

Quite a few AI generated post on this thread.

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Tam said:

AI might be overrated due to the limitations of image recognition. For example, when drones attack an air base for example, the drone is programmed to attack via an image of the aircraft, let's say to target a part. This can fail under some conditions like if the aircraft is a dummy, or the aircraft is junk and nonfunctional, or is a carcass being cannibalized for parts. This can extend to air defense systems, artillery pieces, to even using mannequins. What will stop drones from repeatedly striking the same destroyed vehicle, an entire swarm ends up getting consumed that way. An entire expensive vehicle might have been sacrificed, but the entire assault ends up being successful and the position gets grabbed.

Likewise with enough camouflage, armor add ons, and cope cages, a vehicle can alter it's look to the point that it's no longer recognizable as say, a T-72. On field modifications can make each Turtle Tank visually unique. For AI and image recognition to work, the drone must have preset images of the target stored in it's memory. If a potential target doesn't fit that image, it's going to bypass it.

If we loosen the image requirements to say, let's attack a box with wheels, you risk the drone attacking your own forces. Especially a problem if both sides have similar designs.

Targets hiding in foliage and forest, and with camouflage can also disrupt a visual algorithm.

While AI can be used to gather and spot for potential targets, human intervention may be necessary to prevent hitting dummies, friendlies, already destroyed vehicles, and to verify authenticity of the target.

The more expensive a drone gets, the less attractive it becomes as an option. The more complex a drone gets the more things it's likely to get wrong. The more complex the software gets, the more bugs are likely to happen and the system will suffer increased latencies.

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