What transforms a MEMS sensor into a Tactical-Grade Inertial Measurement Unit (IMU)? The answer lies in a rigorous engineering process that extends far beyond the sensor itself. Discover how calibration, environmental test chambers, temperature cycling, vibration qualification, shock testing, repeatability, and performance verification ensure accurate, stable, and reliable inertial measurements for demanding aerospace and defense applications.
GNSS spoofing has become one of the most significant threats to autonomous navigation systems. Unlike GNSS jamming, spoofing delivers false positioning data that appears completely legitimate, making it far more difficult to detect. This article explains how Sensor Fusion and high-performance IMUs help identify navigation inconsistencies, why inertial navigation has become increasingly important in GNSS-degraded environments, and which IMU characteristics matter most when designing reliable autonomous systems.
Artificial intelligence can decide which drone to track next. But only accurate position feedback and inertial sensing can ensure the system actually gets there. Discover why rotary position sensors, environmental sensors and tactical MEMS IMUs have become essential building blocks of modern Counter-UAS swarm defense.
Detecting a drone is only the first step. The real challenge is keeping it centered within the field of view while both the drone and the sensor platform are moving. This article explains how gyroscopes, inertial sensing, latency, bandwidth, and control loops work together to determine whether a Counter-UAS system maintains reliable target tracking throughout the mission.
What happens when GPS is lost? This article explains why IMU performance becomes critical during GNSS outages, which specifications matter most, and how small angular errors can become meters of navigation and pointing error in real-world applications.
How does an Inertial Navigation System (INS) really work? What happens between an IMU measurement and a navigation solution? This article explains, step by step, how modern INS algorithms estimate attitude, remove gravity, integrate acceleration into velocity and position, fuse IMU and GNSS data with a Kalman Filter, and continue navigating even when GNSS signals are lost. Whether you’re developing UAVs, autonomous vehicles, EO/IR systems, or other mission-critical platforms, this practical guide reveals what happens inside a professional inertial navigation system.
An IMU measures motion-but it does not provide navigation. This technical guide explains how raw gyroscope and accelerometer measurements are transformed into a complete Inertial Navigation System (INS), covering attitude estimation, gravity compensation, velocity and position calculation, Sensor Fusion, Kalman filtering and navigation during GNSS outages.
Why can replacing an identical IMU lead to weeks of recalibration? Learn why Repeatability has become a critical design parameter for modern EO/IR, stabilization, navigation, and APNT systems, and how it helps reduce engineering effort, maintenance costs, and lifecycle risk.
Is Bias Stability really the most important gyroscope specification? In many high-speed stabilization systems, Sensor Noise has a greater impact on image quality. Learn why Noise, Bandwidth, Output Rate, and Latency often determine real-world performance.
Engineers typically compare IMUs based on performance, accuracy, bandwidth, and price. However, one critical factor is often overlooked: ease of integration. A sensor that’s just a few millimeters larger can trigger PCB redesigns, mechanical changes, additional prototypes, and costly project delays. Discover why a compact IMU can reduce integration risk, shorten development cycles, and lower the total cost of ownership- often saving far more than the difference in component price.
