Tag: Gladiator_Technologies

In a High-Dynamic system, the first question is not:

“Which IMU should I choose?”

The first question is:

“What is the most extreme motion the system must accurately measure?”

Once the Dynamic Envelope is clearly defined, selecting a Tactical IMU becomes more than a comparison of numbers in a datasheet. It becomes an engineering decision based on the actual mission requirements.

For demanding Aerospace and Defense applications, this is the key to matching the right High-Dynamic MEMS IMU to the system, rather than simply choosing the sensor with the most impressive specifications.

In mobile Antenna Positioning systems, knowing the antenna position is not enough. Discover how IMU data, Position Feedback, Beamwidth, Latency, and Pointing Error work together to maintain a stable communication link even while the platform is moving.

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.

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.