A Tactical Grade IMU is tested when real-world conditions stop behaving like the lab. Explore how bias, bandwidth, latency, vibration, temperature, GNSS loss and sensor trust determine whether a Tactical IMU is truly right for the mission.
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.
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.
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.
The SX3 architecture represents a new generation of MEMS inertial sensing, combining ultra-low noise, high stability, 600 Hz bandwidth, 10 kHz output rates and sub-20 µs latency in a compact platform. Designed for advanced stabilization, tracking, autonomy and navigation-assisted applications, SX3 demonstrates how modern MEMS technology is evolving beyond traditional motion control toward systems where measurement quality itself becomes a critical factor in overall mission performance.
When evaluating an IMU, many engineers focus on a single specification: update rate. A 2000Hz IMU must be better than a 200Hz IMU – right? Not necessarily. In real stabilization, tracking, and navigation systems, performance depends on much more than output frequency alone. This article explains the critical differences between Bandwidth, Output Rate, and Baud Rate, and shows why an IMU that sends data faster is not always the one that delivers better system performance. Through practical examples from EO/IR gimbals and UAVs, we explore how understanding these three parameters can prevent costly design mistakes and lead to more effective sensor selection.
Two MEMS IMUs with remarkably similar datasheet specifications were evaluated for a high-performance stabilization system. Both offered excellent bias stability, low noise, and impressive inertial performance. Yet one delivered noticeably better tracking, faster settling, and superior image stability. What caused the difference? This case study explores why latency, synchronization, bandwidth, and timing determinism often matter more than traditional navigation specifications when designing EO/IR, gimbal, antenna tracking, and UAV stabilization systems.
Scale factor error quietly distorts motion data long before a system completely fails.
In MEMS IMUs, even small scaling inaccuracies can degrade:
* Navigation accuracy
* EO/IR stabilization
* Dead reckoning
* GPS-denied performance
In high-end inertial systems, accuracy starts at the sensor level.
