Operational Concepts for Modern Drone Deployments

Navigation Without GNSS: The New Operational Standard in Drone Warfare The war in Ukraine has proven that the era of UAVs relying solely on GNSS is over. The battlespace is saturated with electronic warfare systems that disrupt satellite signals across multiple frequencies. In this environment, even advanced CRPA antennas with eight elements have become ineffective. Jamming now comes from multiple directions with overwhelming power, rendering traditional spatial filtering obsolete. A recent case on the Sumy axis illustrates the shift. After a Superkam (Skat) UAV was shot down, investigators found a high-precision altimeter and an onboard microcomputer. This indicates the use of terrain-referenced navigation—specifically, digital elevation models (DEMs) that allow a UAV to determine its position by comparing terrain profiles rather than relying on external signals. Once reserved for cruise missiles (like TERCOM), this technology has now been adapted for tactical drones. This is no longer experimental. UAVs like the V2U have been operating with terrain-matching capabilities for over a year. In parallel, visual navigation using EO or IR cameras with SLAM algorithms is gaining traction. These systems allow drones to localize themselves by comparing live camera feeds to reference imagery, even in complete GNSS denial. Inertial Navigation Systems (INS) provide short-term positional awareness using internal sensors. Though they suffer from drift, they are highly valuable when fused with other data sources—terrain, visual, or barometric. Advanced UAVs now rely on multi-sensor fusion: combining INS, altimeters, EO/IR imagery, and map data to create resilient, redundant navigation systems. A growing trend is local radio-based navigation using pseudo-satellites, RF beacons, or LTE/5G triangulation. In combat zones, however, reliance on national infrastructure is impractical. Instead, tactical forces must create their own positioning grid, using UAVs or ground-based transmitters. This evolution demands a new mindset. Enhancing GNSS resilience is no longer enough. The very architecture of navigation must be rethought. Resilience must come from independence, not reinforcement. Key implications: All medium- and long-range UAVs must support GNSS-free navigation. Terrain and visual databases are now strategic assets. INS and onboard computing are essential, not optional. Command systems must assume operations in GNSS-denied environments as the norm, not the exception. In modern warfare, the winner won’t be the one with the strongest signal—but the one who no longer needs it. Autonomous navigation in signal-denied environments will define next-generation UAV effectiveness. If you’re designing a drone today, the first question should be: How will it navigate when nothing works? Because that is the new baseline.

Controlling 10,000 drones with a single computer is a complex task that involves multiple technologies working together to manage communication, coordination, and flight operations effectively. Here are some key technologies that can be used to achieve this: Swarm Intelligence: Algorithms inspired by social insects like bees or ants can help coordinate and manage large numbers of drones to work together as a cohesive unit. Distributed Computing: Leveraging distributed computing allows processing tasks to be shared among drones, reducing the load on a single computer. Cloud Computing: Using cloud infrastructure can provide the computational power and storage needed to process large amounts of data and commands for the drones. Real-time Communication Protocols: Efficient protocols, such as MQTT (Message Queuing Telemetry Transport) or DDS (Data Distribution Service), support low-latency communication between the control system and drones. Mesh Networking: This network topology enables drones to communicate with each other directly, forwarding data to extend range and reliability. AI and Machine Learning: AI algorithms can optimize flight paths and decision-making, enhancing the ability to manage large drone swarms. GPS and GNSS: These systems provide precise location data necessary for coordinating drone movements and ensuring they follow the correct paths. 5G Connectivity: High-speed, low-latency networks like 5G can significantly improve communication between drones and the control computer. Edge Computing: Processing data on the drones themselves can reduce latency and bandwidth by only sending essential data back to the main control system. Autonomous Navigation Systems: Technologies such as SLAM (Simultaneous Localization and Mapping) allow drones to navigate independently, reducing the control load. Simulation and Digital Twin Technology: These tools help model and plan drone missions effectively, optimizing performance and reducing risks before deployment. Integrating these technologies can enable effective management of large drone fleets, allowing for coordinated operations across various applications, from logistics to surveillance.

🎯 Rotation Denial and Sensor Dominance Along the Line of Contact   The attached footage demonstrates UAV operations conducted simultaneously across various groupings along the line of contact. It is important to note that the focus here is not on individual strikes, but rather on the range of sensors, targets, and roles functioning within the same battlespace.   🔍 What the Video Actually Shows   🚗 Target Profile The majority of strikes target soft-skinned vehicles, civilian cars, and lightly modified platforms with add-on protection. There is a notable absence of standard armored personnel carriers (APCs), infantry fighting vehicles (IFVs), or protected motorized vehicles (such as MRAP-class platforms). This trend suggests that survivability is now influenced less by the type of platform and more by whether movement is detected at all.   🌡️ Multi-Spectral Detection Targets are identified and struck using both RGB optics and thermal imaging, which significantly reduces options for concealment and minimizes the survivability gap between day and night operations.   🛰️ Layered UAV Roles - Strike drones engaging ground targets. - Counter-UAV drones intercepting other drones in an air-dominance role. - High-resolution reconnaissance UAVs providing long-range detection and target cueing.   These roles are not separate missions; they function as a continuous sensor-shooter loop.   🚶 Movement as the Trigger Most engagements happen during rotations, resupply operations, or repositioning, rather than during deliberate assaults. Units are targeted because their movement is detected, not necessarily because they are actively attacking.   📌 Operational Takeaway Attrition is no longer primarily caused by assaults on prepared positions; it increasingly results from attempts to move forces under constant aerial observation. Low-altitude airspace has become permanently contested. UAVs serve simultaneously as sensors, shooters, and targets, while higher-end reconnaissance platforms extend detection capabilities beyond visual range.   In this environment, the decisive factor is no longer the thickness of armor or the category of the vehicle; it is the exposure time within a saturated sensor-shooter system. This represents a shift from traditional strike warfare to a focus on area control through persistent detection.   #MilitaryAnalysis #DroneWarfare #UAV #ModernWarfare #OperationalArt #BattlefieldDynamics #DefenseAnalysis

The rapid rise of combat drones illustrates a classic pattern described by Clayton Christensen. Drones represent a 𝐥𝐨𝐰-𝐞𝐧𝐝 𝐝𝐢𝐬𝐫𝐮𝐩𝐭𝐢𝐯𝐞 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲: initially dismissed as inferior to established systems, yet capable of reshaping the entire competitive landscape. For decades, the Western defense industry focused on increasingly sophisticated missiles, precision bombs, and air-defense systems. These technologies became extremely advanced—and extremely expensive. In that environment, small and relatively crude drones seemed strategically irrelevant. Yet disruption often starts exactly there. Take the Iranian Shahed drones now widely used in conflicts. They are cheap, simple, and can be produced in large numbers. Their real power lies not in individual performance but in scale and swarm tactics. When launched in large waves, they overwhelm traditional air-defense systems designed to intercept a limited number of high-value missiles. Using million-dollar interceptors against drones costing a few tens of thousands of dollars is economically unsustainable. This is classic Christensen logic: incumbents optimize for high-end performance while the disruptive technology improves rapidly in a different dimension—in this case cost, scalability, and operational flexibility. But the real lesson is not only technological.Ukraine has shown that the decisive capability lies in how drones are used: agile combat strategies, distributed command structures, and operators who can adapt in real time. Human intelligence, battlefield learning, and tactical creativity matter as much as the hardware itself. It all has to go together. For Europe and the wider West, the implication is that defense strategies must shift from a narrow focus on expensive platforms toward learning systems that combine low-cost technology, rapid experimentation, and shared operational intelligence. And this knowledge already exists: Ukraine today is probably the world’s most advanced laboratory for drone warfare. Western militaries should accelerate collaboration and learning from that experience. The rise of low-cost drones and other low-end digitalized warfare technologies also forces a reconsideration of how military budgets are optimized. Rather than automatically increasing defense spending, the priority should be to reassess how military effectiveness can be maximized by reallocating resources—shifting a larger share of investment toward scalable, low-cost systems such as drones. #DisruptiveInnovation #Drones #MilitaryInnovation #DefenseStrategy #Ukraine #Security #ClayChristensen #DroneWarfare

With the current impact of cell network outages across almost all carriers in the US, it's a good time to talk about the future; actually, it's not even about the future, it's the present. Several years ago I started talking about having mobile robotics (air, ground and maritime robotics, like drones, rovers and submergible devices) be part of a mobile adhoc network or MANET. One example is a private mesh network, like Silvus Technologies provides. These communications solutions for high bandwidth video, C2, health and telemetry data are absolutely needed in today's environment and allow for a very flexible set-up and coverage; from a local incident scene, to a much larger area coverage, to entire cities or counties being covered. Why the need? While we in the drone industry originally focused on getting drones connected to a cell network, we quickly realized the single point of failure; the cell network infrastructure. Natural disasters, as well as manmade disasters, can impact these networks dramatically. An earthquake, hurricane, a solar storm, or a cyberattack, can take down these public networks for hours to days. And that includes public safety dedicated solutions like FirstNet or Frontline, during times when coms and data push is absolutely needed. Over the past couple of years we have seen the rise of mobile robotics deployments within private networks. While the defense side has done this approach for years, the public safety sector is still new to this concept. Some solutions integrate with a variety of antennas, amplifiers and ground stations, offer low latency, high data rates (up to 100+Mpbs), 256-bit AES encryptions and allow for a very flexible and scalable mobile ad-hoc mesh network solution. And most importantly - independence from a public network system. And now imagine you have multiple devices operating; a helicopter, a drone, a ground robotic, together with individuals on the ground, all connected and all tied into a geospatial information platform, like ATAK/TAK. Each connected device can become a node and extend the range. This is what I am calling building the Tech/Tac Bubble. This is not just the future, this is already happening with a handful of agencies across the US It's time to start thinking about alternative communication solutions and mobile robotics are an important part of leading the way. #UAV #UAS #UGV #Drones #network #MANET #Meshnetwork #publicsafety

⚠️ NOT EVERY UAV IS BUILT FOR THE SAME WAR... One of the biggest misconceptions in the drone debate is treating all UAVs as if they solve the same problem. In reality, different platforms exist because operational requirements are fundamentally different. 🛩️ FIXED WING SYSTEMS PRIORITIZE RANGE AND ENDURANCE. They are optimized for ISR, surveillance, mapping, border monitoring, and long duration missions. Their strength is efficiency over distance, but they usually require more space, infrastructure, and operational planning. 🚁 MULTIROTOR PLATFORMS PRIORITIZE FLEXIBILITY. They dominate inspection, logistics, tactical reconnaissance, urban operations, and short range precision tasks. They are highly maneuverable and easy to deploy, but limited in endurance and range. ⚙️ VTOL HYBRID SYSTEMS TRY TO COMBINE BOTH WORLDS. These systems are becoming increasingly important because they combine vertical takeoff capabilities with the efficiency of fixed wing flight. Especially in logistics, military mobility, and remote area operations, this category is gaining significant relevance. 🔥 FPV SYSTEMS CHANGED THE MODERN BATTLEFIELD. Originally rooted in racing communities, FPV drones have evolved into highly agile and low cost tactical systems. Their speed, maneuverability, and adaptability created entirely new operational dynamics in reconnaissance and strike missions. 🧠 THE REAL SHIFT IS HAPPENING AT THE SYSTEM LEVEL. The future is no longer about individual drones alone. It is about autonomous coordination, swarm logic, AI supported mission planning, sensor fusion, and scalable man machine teaming. A single drone can provide information. A connected ecosystem creates operational advantage. 🚀 The important question is no longer whether autonomous systems will shape the future. The question is how fast organizations can adapt their structures, doctrine, training, and decision making to integrate them effectively.

What happens to a drone when the signal disappears? No GPS. No uplink. No cloud fallback. Does it hover and wait? Or abort the mission? Or continue with confidence? That's where autonomy matters... Obstacle avoidance in clean conditions is easy. But operating under constraint is not. And that's why drones can learn something important from submarines. Submarines operate in environments where communication is intermittent, positioning is uncertain, and surfacing for correction is risky. So their autonomy is built on 3 major principles: 𝟏. 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐥 𝐍𝐚𝐯𝐢𝐠𝐚𝐭𝐢𝐨𝐧 𝐃𝐢𝐬𝐜𝐢𝐩𝐥𝐢𝐧𝐞 They rely on inertial systems and continuous internal state estimation. They don’t depend on constant external correction. 𝟐. 𝐑𝐞𝐝𝐮𝐧𝐝𝐚𝐧𝐭 𝐒𝐞𝐧𝐬𝐢𝐧𝐠 Acoustic, inertial, and environmental signals are fused to maintain awareness even when one channel degrades. 𝟑. 𝐄𝐧𝐞𝐫𝐠𝐲-𝐂𝐨𝐧𝐬𝐜𝐢𝐨𝐮�� 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐌𝐚𝐤𝐢𝐧𝐠 Every maneuver considers power, mission duration, and survivability. Modern drones entering contested airspace, dense urban zones, or GPS-degraded regions are facing similar constraints. They need: Robust onboard state estimation Multi-layered sensor fusion Memory of mission context Predictive confidence modeling Graceful degradation under uncertainty At 𝐕𝐢𝐦𝐚𝐧𝐚, that's why we prioritise autonomy as structured independence. Submarines teach us, true autonomy is the ability to continue intelligently when the environment stops cooperating. That’s the difference between a connected drone and a dependable one. #AutonomousSystems #Drones #Robotics #AerospaceEngineering #ArtificialIntelligence #Vimana

Came across a video of a vehicle roof-deployed #UAS system integrated into a BYD —obviously not in the U.S. What really caught my attention is that this was done in partnership with DJI . As expected, my imagination immediately started running wild. Yes, I know there are already solutions in use today. We’ve seen tethered systems like Fotokite and drone docks mounted in pickup truck beds. All solid concepts. But none of them are fully integrated into a single, purpose-built platform quite like this. What makes this interesting is the level of integration and immediacy. A system that’s always with the vehicle, protected, charged, and ready to deploy at a moment’s notice—no cases to open, no setup time, no delay. The public safety applications are endless. Fire overwatch deployed directly from a command vehicle. Law enforcement response where a drone could launch automatically via a body-worn camera activation for fleeing suspects or missing persons. Faster situational awareness, better decision-making, and less risk to responders on the ground. This is the kind of thinking that pushes #DFR and mobile UAS forward—not just flying drones, but embedding them into the response ecosystem itself. And this is where the concern comes in. With recent Federal Communications Commission bans and restrictions, the unintended consequence is that we risk leaving ourselves years behind while the rest of the world continues to innovate, integrate, and deploy systems like this at scale. While others are building fully integrated response platforms, we’re busy navigating limitations that slow progress instead of accelerating it. The question isn’t if we’ll see systems like this adopted in public safety—it’s how long it will take, and whether we’ll be leading that evolution or struggling to catch up. #LawEnforcement #Police #FirstResponders #PublicSafety #DronesForGood #Drones #TechForGood #DJI #BYD

It looks like something straight out of science fiction—but this actually happened in real life in 2021. The DARPA “Gremlins” program has demonstrated a remarkable capability: a drone launched into the sky, then recovered mid-air by a C-130 Hercules—hooking onto a system, folding its wings, and being safely pulled back inside… all without landing. This isn’t just a technological spectacle—it signals a fundamental shift in how airpower can be generated and sustained. Imagine aircraft no longer as single-mission platforms, but as airborne hubs capable of deploying, coordinating, and recovering multiple UAVs within a single sortie. Missions become more flexible, risks are distributed, and assets are no longer strictly expendable. The real breakthrough here is not just recovery—it’s reusability and rapid turnaround. As programs like Skyborg evolve, we are moving toward a future where pilots don’t just fly aircraft—they manage intelligent, autonomous teams in the sky. This raises an important question for the global aerospace and defence ecosystem: If aircraft can now deploy and “catch” drones mid-air, how far can this concept scale? • Airborne drone carriers • Swarm-based operations • Deep strike without pilot exposure • Continuous ISR and electronic warfare cycles We may be witnessing the early stages of a new doctrine—where one aircraft can generate the combat power of many.

Walk into any drone expo, and everything is shiny, blinking, and impressive…but, Almost nobody asks: What outcome does this actually deliver? We’ve built an industry that’s very good at showcasing technology. New payloads. Smarter sensors. More automation. Bigger specs. And to be clear, innovation is good. But enterprise buyers don’t scale programs because something looks impressive on a booth floor. They scale programs because it solves a business problem. I was reminded of this before a podcast recently. I said, “They make drones.” When I should've said. They built connectivity infrastructure. And that mistake says a lot because the real value often isn’t the aircraft you see… It’s the operational outcome it enables. That’s the mindset shift I keep seeing between early-stage programs and mature enterprise operations: ❌ Technology-first thinking ➡️ “What can this drone do?” ✔️ Outcome-first thinking ➡️ “What business result are we trying to achieve?” The mature approach is simple: Start with the outcome. Define the operational problem. Then reverse-engineer the technology stack needed to achieve it. Not the other way around. Because once you focus on outcomes, the questions change: • Does this improve uptime? • Does it reduce operational risk? • Does it shorten decision cycles? • Does it actually move ROI? Shiny technology gets attention. Clear outcomes get budgets.