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Prism A-ISR

Model: 110-0201-92
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In Production
Prism™ A-ISR is AI-enabled airborne intelligence, surveillance, and reconnaissance (ISR) software for real-time ground object detection, classification, and tracking from uncrewed aircraft systems (UAS) and other aerial platforms. Using thermal infrared and electro-optical (EO) sensor data, Prism A-ISR supports air-to-ground object detection, AI-based object classification, and real-time tracking in cluttered or degraded visual environments. It combines patented image processing, AI perception models, multispectral training data, and edge processing expertise to improve long-range situational awareness while reducing false alarms and integration risk.

The software supports passive, multi-object detection and tracking for persistent surveillance, force protection, and intelligence missions. Custom object classes and updated AI models can be generated with AIMMGen™ synthetic model-training services, helping developers adapt to evolving operational needs.

Built for OEM integration and scalable deployment, Prism A-ISR supports 14-bit longwave infrared (LWIR) and midwave infrared (MWIR) data from Teledyne FLIR Boson® and Neutrino® thermal camera families, including fixed focal length and continuous zoom (CZ) configurations, as well as third-party infrared and visible EO cameras. Designed for NVIDIA Orin and Qualcomm 8550 embedded AI platforms, Prism A-ISR helps developers add mission-ready EO/IR perception and real-time object tracking to next-generation airborne ISR systems.
 

ENHANCED DETECTION AND TRACKING

Extend detection range, improve track persistence, and reduce false alarms

  • Patented denoise and super-resolution improves signal to noise
  • Electronic stabilization and dehaze algorithms improve image quality
  • Patented denoise algorithm minimizes bit rate
 

STREAMLINE LWIR, MWIR, AND EO CAMERA INTEGRATION

Native support for Boson+, Boson SX8, and Neutrino series accelerates deployment

  • Supports 640 × 512 and 1280 × 1024 LWIR and MWIR resolutions
  • Compatible with fixed focal length and CZ lens configurations
  • Accepts 14-bit IR-camera data 
  • Delivers frame-rate perception on EO resolutions up to 4 MP
 

BUILT FOR DEVELOPERS AND DEPLOYMENT

Lower integration risk with production-ready technology, developer tools, and expert technical support

  • Sample C++ reference application, libraries, and documentation
  • Experienced technical services team supports integration and deployment
  • Operates on Qualcomm and NVIDIA embedded hardware
  • Adapt models for new missions with Prism AIMMGen™ synthetic data

Specifications

Performance Metric

Included Filters
Denoise, Super Resolution, Electronic Stabilization
Inference Time
~10 ms
Input Wavelength
EO, MWIR, and LWIR
Metadata Output
Bounding Box Area
Bound Box Location
Category ID
Object Class Label
Confidence
Time Stamp
Track ID
Frame Number
Object Classes - Infrared and EO
Person, vehicle (umbrella class car, bus, truck, van, construction), boat (umbrella class for all types of vessels on water)
Object Classification >60% Confidence
≥10x10 Pixels on Target (minimum)
Simultaneous Targets Tracked
Maxuimum is System Dependent, Default is 16, Configurable
Target Detection Confidence Threshold
≥60% for Small Targets (<32 x 32 pixels), Configurable

System Requirement

Deliverables
• User Graphical Interface (GUI)
• Software Development Kit (SDK) with Prism A-ISR solution package
• Technical Documentation
EO Camera
4 MP with UVC Input Typical
(larger format will affect frame rate)
Hardware
NVIDIA ORIN NX/AGX, Qualcomm 8550
IR Cameras
Boson+ with UVC
Boson SX8 with UVC
Neutrino LC with USB
Neutrino SX8 with USB
Power
<12 W (average)
<15 W (maximum)
Video Output
WebRTP, RTSP, and HDMI

Resources & Support

Assets below are shared by all models in this product family.

Prism A-ISR Datasheet

Datasheet

Download

Integrating Teledyne FLIR OEM thermal camera modules is easier than ever with our library of how-to videos and more!

Deploying AI Object Detection, Target Tracking, and Computational Imaging on Embedded Processors
Introducing FLIR AVP
Integrate AI Decision Support with Prism AI
Guide to Image Signal Processing with Prism ISP
How to Optimize MWIR Performance and Computational Imaging to Simplify Integration
Prism SKR Explained: End to End Target Detection, Tracking and Homing

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