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MEMS vs FOG: what inertial system should you choose?

Stephane RecouvreurBy Last edited June 8th, 2022No Comments

MEMS vs FOG: the Ring laser gyroscope (RLG) has dominated the inertial navigation market since its first inception in 1963, recently its dominance has been challenged by improvements to Fibre Optic Gyroscopes (FOG) technology. These technological improvements are slowly but surely eroding the RLG’s place in the inertial navigation market, pushing the aging technology to irrelevance.

Is this cycle about to be repeated with MEMS?

This is a legitimate question, given how far the technology has come in recent years, with MEMS gyro sensors achieving better accuracy, improved error characteristics, and better g-sensitivity that drastically improved overall MEMS performance. The two technologies now often go head-to-head for tactical and navigation grade applications with no clear winner.

Picking an inertial technology used to be a straightforward decision, but as the competition between the two approaches heats up, navigation engineers are now forced to take many considerations into account based on their specific application before settling for either solution.

FOG still dominating for critical applications

Fibre is still the tried and tested solution for high-end applications, slowly replacing the aging RLG technology wherever possible. The technology has still unmatched performance, thanks to its very low noise fibre-optic gyroscopes, enabling extremely accurate navigation, and low bias instability and drift relative to other technologies, essential to staying on track in GNSS denied environments.

FOG INS is indeed considered better suited for critical navigation solutions such as deep-sea underwater navigation and aerospace applications. While its high cost makes it prohibitive for the lower end of the market, less price-sensitive end-users such as the military and commercial aircraft manufacturers are happy to pay more for the added extra accuracy. Its inherent lower drift also makes it the preferred choice for long-term GNSS denied applications, as the overall error margin is lower than even the most accurate MEMS INS available. 

With their solid-state and absence of moving parts, FOGs are also ideally positioned for stealth operations where any kind of low-frequency vibrations can give away their position to the enemy. This is particularly true against older mechanical inertial navigation systems, but less so against the new generation of MEMS that now provide negligible levels of vibrations for this type of application. 

Another feature unique to FOG that makes this technology so attractive is its north-seeking capabilities, even in highly magnetic environments. Contrary to MEMS technology that relies on magnetometers to get accurate heading, FOG precisely measures the earth’s rotation angular rate, even while being in motion, and are able to accurately determine north heading within minutes. This is a particularly sought-after feature for subsea applications that cannot rely on any GPS signal for long periods of time.

Both FOG and MEMS accuracy are impacted by variations in temperature. This problem is typically mitigated by calibrating the system through a range of extreme temperatures. However, note that proper calibration of MEMS can be more difficult due to their mechanical nature. FOG, properly insulated and calibrated, will perform better.

Finally, FOG INSs are not immune to errors in vibration-prone environments. However, because FOGs do not have any moving parts, they can handle vibrations better than their MEMS counterparts. FOG is therefore the preferred approach with heavy equipment stabilisation for mining and industrial applications and aerospace, where aircraft, and notably their wings, are subjected to a very high level of vibration.

MEMS closing the gap between price and performance

Micro-electromechanical systems (or MEMS) have made rapid advances since early concepts dating as far back as the 1950s. Made of tiny integrated circuits and silicon-based microelectronics, the technology has dramatically revolutionised industrial and consumer electronics alike, including inertial navigation systems with the creation of a variety of inertial sensors, including gyroscopes, accelerometers, and magnetometers.

By far, the main benefit of MEMS is its extremely low price compared to its FOG counterparts, sometimes by a factor of 10 for similar or lower performance. The use of less expensive materials, better processes, and smaller size have all contributed to MEMS being cheaper to produce and fuelled its adoption for applications where FOG is simply too cost-prohibitive to make commercial sense, such as in-car GPS, drones, or camera pointing.

MEMS devices are also very small and lightweight. While FOGs are relatively bigger and heavier, preventing their use in tight spaces such as smartphones and toys, for example, MEMS is the perfect solution for space-constraint applications where “good-enough” performance is sufficient. MEMS are now found everywhere, from consumer to industrial-grade applications in a wide range of industries. This small size factor notably fuelled the adoption of MEMS in the drone surveying market, notably LiDAR surveying, where a higher degree of accuracy is needed while remaining relatively small and lightweight to fit on a drone is paramount.

MEMS are also less power-hungry than FOG, allowing for longer mission time for fuel-constrained vehicles. Combined with their small size and lightweight properties, MEMS is the solution of choice for many unmanned vehicles that require the lowest SWaP-C (size, weight, power, and cost) possible.

MEMS accuracy particularly shines in predictable dynamic environments, where the overall behaviour of the vehicle is expected, with no sudden drastic change of attitude or direction that would confuse the internal dynamic motion model constraints that guide the filter to output data. If assisted with external sensors (speed odometer, etc), the overall solution can be a great fit for ground vehicles for example, where a change of speed and direction are relatively expected.

MEMS though is not without its limitations. Due to its mechanical nature and components vibrating at a high frequency, MEMS are more sensitive to vibrations, especially at harmonic frequencies. Vibrations can increase the noise of a sensor output signal, causing a bias that needs to be corrected via software.

This issue can have some practical consequences. A non-negligible number of drone gyroscopes have been found to have resonant frequencies in both the audible and ultrasonic frequency ranges, making them vulnerable to loudspeaker noises. Therefore, it is possible to crash a drone at distance via a “sonic attack” using speakers set at the right frequency.  

MEMS are also typically prone to g-sensitivity errors in gyroscope measurements due to linear acceleration, leading to large biases directly affecting the accuracy of attitude estimation in an INS. While acceleration is often short – just a few seconds – but intense – 5g or more in highly-dynamic fields such as guided weapons and unmanned aerial vehicles, the accumulation of errors over time cannot be neglected, and need to be compensated for. Corrections are done at the filter level but add another degree of complexity that FOG alternatives are simply not subjected to. 

The MEMS vs FOG verdict

Not all FOG and MEMS solutions can be fairly compared with each other, as the difference in price and performance can be simply too important. However, comparing low-end FOG with high-end MEMS is where things get interesting, and where additional considerations such as size, application, etc need to be taken into account.

Ultimately, of the two systems, FOG will always offer the highest level of performance possible. The real question is: how much are you willing to pay for it?


Criteria MEMS FOG
Price Cheap Expensive
Bias Instability Good Best
Initial Bias Poor Excellent
Size Small Larger
Power Low High
Heading Magnetic North Seeking
Magnetic Interference Yes No
Acceleration & Vibration Good Best
G-Force Error Yes No


Application MEMS FOG
Drone/UAV Low payload, cheaper, low power, small size
Subsea Best attitude accuracy, north-seeking, better bias stability
Aircraft  Better bias stability
Ground Vehicle Cheaper, better performance in a predictable dynamic environment
Marine Easy set up (i.e. GNSS Compass) Best attitude accuracy, north-seeking, bias stability
Car Racing Smaller, lower power, good g-resistance
Surveying Small size, low power Best performance