Juniper Defense is developing a multi-sensor drone detection system designed to identify UAVs operating in coverage-challenged conditions, using sensor fusion and machine learning to improve reliability across real-world sites.
We publish performance claims only after validation in representative testing.
Designed for drones operating close to terrain and structures, where clutter, line-of-sight breaks, and noise can create detection gaps.
Combining acoustic and additional sensing inputs (as available) to strengthen confidence, reduce false alarms, and adapt to site-specific conditions.
Designed to scale from single-site pilots to multi-site deployments with centralized monitoring and flexible integration paths.
The system is designed around robust detection in real-world conditions. Our focus is practical deployment: site variability, operational noise, and scalable monitoring workflows.
We prioritize reducing false positives and improving consistency across changing environmental conditions.
Designed for real monitoring workflows: multi-zone sites, centralized visibility, and clear escalation paths.
Iterating on sensing and processing architecture.
Collecting and curating data for evaluation and model iteration.
Seeking pilot partners for representative test environments.
Note: This site describes technology under development. Details may change as testing and validation progress.
We combine evidence from multiple sensing inputs (where available) to improve confidence and reduce false alarms. The goal is robust performance across diverse sites, not reliance on a single signal source.
Not yet. We’re in development and engaging with pilot partners and advisors to validate requirements, environments, and deployment constraints.
A pilot typically involves a limited deployment at a representative site, defined success criteria, and structured feedback. We align on scope, constraints, and data-handling upfront.
Yes—after validation in representative testing. We avoid publishing claims that can’t be supported by real measurements.
Founded by engineers focused on sensing, machine learning, and security-oriented system design.
Edge processing, sensing architecture, deployment constraints.
Fusion strategies, classification, testing methodology.
Pilot execution, stakeholder feedback loops, scalability planning.
Interested in early access, pilots, or collaboration? Send a short note and we’ll respond.
Tell us your environment and timeline. We’re prioritizing pilots that provide representative test conditions.
We’ll follow up by email. Your email address is not displayed publicly on the website.