INS-GPS Based Solution for Personal Navigation

Traditionally, inertial navigation has been an expensive technology which limited its application to high-end military vehicles, precision guided missiles or aircrafts. Since the advent of MEMS technology and low cost gyroscopes and accelerometers, inertial navigation is now being deployed even in cost sensitive & low-powered applications such as for soldier and personal navigation.

One might wonder why inertial navigation is required for soldiers, emergency responders or other persons when one can make do with GPS navigation. It is important to understand that though GPS navigation is now easily available at a very nominal price, it is not advisable to solely rely on it.

Following are some shortcomings of the GPS based personal navigation systems:

Poor or no indoor coverage: GPS signals can be extremely poor in strength in the indoor environment. As a result, tracking soldiers, firefighters or other emergency responders when they are inside becomes difficult. The signals are even poorer in multistoried structures or underground bunkers.

Possibility of spoofing / jamming: Location data of soldiers or undercover personnel could be extremely critical to success or failure of military actions. GPS signals are prone to spoofing (resulting in incorrect information) and jamming (resulting information loss) which can jeopardize the critical missions and may even lead to destruction of human assets.

INS-GPS systems for personal navigation

Aeron’s Castor MEMS-INS (under development) is an extremely low powered, micro- form factor position sensor that runs proprietary machine-learning algorithms fusing data from accelerometers, gyros and GNSS to lend real-time location of personnel and vehicles.

Castor’s adaptive filtering algorithm detects zero velocity, performs real-time calibration of soldier’s step size as well as tracks last known position to generate seamless navigation data even in indoor environment. Figures demonstrate the motion sensor plots when the user is walking, motion rate analysis and step count increasing with time.