AI - Axellio Insights

How Distributed Sensor Ingest Enables True Multi-Domain Operations

Written by Scott Aken, CEO | Sep 21, 2026, 4:30:59 PM

In multi-domain operations, siloed data creates operational challenges and potentially imperils mission effectiveness.

Take for example the 2025 Bamboo Eagle exercise, which involved 10,000-plus personnel and more than 175 aircraft, all operating under a single command-and-control (C2) structure. Running that exercise meant reconciling RF and electronic-warfare data, airborne radar and battle-management feeds, and network telemetry pulled from multiple aircraft, each arriving in a different format and classification level.

Fusing that volume of dissimilar, differently-classified traffic into one coherent picture ­— in near-real time, amidst adversarial jamming — outstrips manual correlation efforts. It demands a purpose-built infrastructure.

The problem is only getting worse. “The next generation of wide-area motion imagery sensors is projected to have the capability of collecting 2.2 petabytes of data each day, which is more data than if someone recorded high-resolution video 24 hours a day, seven days a week, for nearly seven years,” Deloitte predicted in 2023. That expectation is rapidly becoming reality.

The Center for Strategic and International Studies (CSIS) sees this playing out in the Ukraine war, where Ukraine's Delta system provides military intelligence with video, photo, acoustic, and text data streams in tens of terabytes daily. There's value in that data, but as CSIS notes, "combining and integrating insights from diverse sources, including imagery, signals, and other types of intelligence, presents an intricate puzzle for military analysts."

For program managers, systems architects, ISR/SIGINT planners, and joint force integrators, multi-domain operations depend on a unified picture. But sensor data today is captured and stored in domain-specific silos — RF here, network there, telemetry somewhere else. The military needs new solutions to overcome the challenge.

Today’s Data Silos — Why RF, Network, and Telemetry Live Apart

Fragmentation comes with a cost: It can delay or interrupt mission effectiveness. How did we get to this perilous moment? There are historical and technical reasons for the current, siloed data situation. 

The military has deployed different sensor types as missions have evolved. These in turn handle data in different formats. Each domain has built its own point solution, optimized for its own capture problem. That can be effective locally, but that high degree of fragmentation creates challenges globally. Consider for example three data types:

  • RF (IQ): Raw in-phase/quadrature samples captured continuously at high sample rates. Time-domain waveform data with no inherent structure, or framing. Massive volume even for short capture windows.
  • Network/packet: Discrete, self-describing units (headers, protocols, addressing) arriving asynchronously and in bursts. Structured but heterogeneous — format varies by protocol, encapsulation layer, and classification tagging.
  • Telemetry/time-series: Regularly sampled scalar or vector values (position, status, sensor readings) at comparatively low rates. Highly structured, schema-driven, but sparse relative to RF and packet volumes.

The fusion challenge: These three data types differ in sample rate, structure, and semantics. Correlating wildly different volumes and formats onto a common, queryable time base can be significantly challenging, if even possible. Point solutions don't solve this architectural problem.

There is an urgency around solving this challenge, according to researchers at the U.S. Government Accountability Office (GAO). “DOD expects that, while difficult, pursuing CJADC2 will enable key decision makers to share and use data to perform command and control operations more quickly and easily,” they note. “For example, CJADC2 would support a transition from a model where an analyst receives inputs and manually enters data from different systems — referred to as ‘swivel chair’ analysis — to a model where all data is integrated.”

That’s the potential win. And there’s an operational price to be paid if the Pentagon does not act swiftly on this.

The Operational Cost of Fragmented Intelligence

This fragmented situation has a direct mission impact. Silos mean operators will see delayed correlation across domains. Analysts have to manually stitch together timelines, and risk missing cross-domain indicators (e.g., an RF emitter correlating with a network anomaly that no one connects in time).

Risks include:

  • Delayed decision cycles
  • Analyst overhead / manual correlation
  • Blind spots at domain boundaries
  • Inability to replay a joint mission picture after the fact

The GAO's April 2025 report on JADC2 identified a fundamental institutional problem: The Pentagon has not yet established a comprehensive framework to guide its various C2 efforts. Fragmentation at the sensor-capture layer contributes directly to that gap. The military needs a converged sensor-to-shooter picture.

True Convergence Requires Architecture, Not Just Tools

It’s not enough to store RF and network data in adjacent systems. They need a common time base, common query interface, and simultaneous read/write across domains. Specifically, they need:

  • A common time index — Every I/Q sample, packet, and telemetry point timestamped and queryable together.
  • Unified ingest at the edge — Capturing multiple sensor types simultaneously without dropping data.
  • Cross-domain query and replay — The ability to pull an RF signature and correlated network/telemetry activity from the same window, together.

SensorXpress and the Xpress Platform offer a way for commanders to solve this crucial problem, by unifying time-series data and eliminating the silos that can hinder mission effectiveness.

SensorXpress is built to capture RF/I/Q and sensor telemetry at speed. Because it sits on the same Xpress Platform as PacketXpress, RF and network data share a storage/query/replay layer — instead of living in separate silos.

This hardware-agnostic solution delivers edge-to-rear deployment consistency. It’s the same architecture in a forward-deployed rack or a rear-area center.

Mission Impact

This modernized approach delivers tangible outcomes in terms of decision support outcomes.

Instead of surfacing partial insights from fragmented data, analysts and mission planners get one place to query, correlate, and replay across domains. Instead of hopping between systems, they can gain  real-time access to the actionable intelligence that drives mission success.

Conclusion

In multi-domain operations, it isn’t enough just to capture data. These missions succeed or fail depending on whether data converges fast enough to be useful.

From satellite networks to tactical edge operations, Axellio supports mission-critical environments with secure, real-time data intelligence solutions – turning fragmented sensor data into mission-ready insight when it matters most.. To explore how SensorXpress and the Xpress Platform can enhance your organization’s operations, reach out through axellio.com.

 

Frequently Asked Questions

What is multi-domain sensor data fusion?

It's the ability to correlate RF/IQ, network/packet, and telemetry/time-series data, captured at different rates, structures, and classification levels, on a common, queryable time base, so analysts can see one picture instead of reconciling separate systems by hand.

Why do RF, network, and telemetry data end up in separate silos?

Each sensor type evolved its own point solution optimized for its own capture problem. RF/I/Q, packet, and telemetry data differ in sample rate, structure, and semantics, so storing them in adjacent systems still leaves them fragmented rather than converged.

How does CJADC2 relate to this challenge?

The Combined Joint All-Domain Command and Control (CJADC2) initiative aims to let commanders share and act on data across multiple domains faster. GAO has found that DOD has not yet established a comprehensive framework to guide its C2 efforts, and fragmentation at the sensor-capture layer is part of that gap.

How do SensorXpress® and the Xpress Platform® address the problem?

SensorXpress captures RF/I/Q and sensor telemetry at speed and sits on the same Xpress Platform® as PacketXpress®, so RF and network data share a common storage, query, and replay layer instead of living in separate silos with the same architecture from a forward-deployed rack to a rear-area center.