###### Educational Material

# 1.7 GNSS-Aided Inertial Navigation System (GNSS/INS)

Learn more about system contributions, system fusion, and the challenges of GNSS/INS.

The Global Navigation Satellite System (GNSS) is a satellite configuration, or constellation, that provides satellite signals to a GNSS receiver which can be used to calculate position, velocity, and time. An inertial navigation system (INS) uses an inertial measurement unit (IMU) consisting of microelectromechanical system (MEMS) inertial sensors to measure the system's angular rate and acceleration. These IMU measurements can then be used by the INS to determine the attitude, position, and velocity of the system. Measurements from each of these two systems can be combined using advanced Kalman filtering estimation techniques to form a GNSS-aided INS system (GNSS/INS). This combined system is able to provide position, velocity, and attitude estimates of higher accuracies and with better dynamic performance than a standalone GNSS or INS system can provide. GNSS and INS can be combined using MEMS inertial sensors, a high-sensitivity GNSS receiver, and advanced Kalman filtering and algorithms to form a GNSS/INS system. Measurements from the GNSS receiver are coupled with measurements from the inertial sensors to provide position, velocity, and attitude estimates of higher accuracy and with better dynamic performance than a standalone GNSS or INS system can provide.

## System Contributions

A GNSS/INS system typically includes a 3-axis gyroscope, a 3-axis accelerometer, a GNSS receiver, and sometimes a 3-axis magnetometer to estimate a navigation solution. Each of these sensors contribute different measurements to the GNSS/INS system.

### Gyroscope & Magnetometer

Both the gyroscope and magnetometer provide a GNSS/INS system with the same contributions that they provides to an AHRS. The gyroscope angular rate measurements are integrated for a high-update rate attitude solution, while the magnetometer (if used) provides a heading reference similar to a magnetic compass. More information regarding the contribution of these sensors can be found in Section 1.6.

### Accelerometer

An accelerometer in a GNSS/INS system measures both the system's linear acceleration due to motion and the pseudo-acceleration caused by gravity. To obtain the system's linear acceleration due to motion, the pseudo-acceleration caused by gravity must be subtracted from the accelerometer measurement using estimates of the system's attitude. The resulting linear acceleration measurement can then be integrated once to obtain the system's velocity and twice to obtain the system's position. However, these calculations are heavily dependent on the INS maintaining an accurate attitude estimate, as any error in the attitude causes an error in the calculated acceleration, consequently causing errors in the integrated position and velocity.

### GNSS Receiver

A GNSS receiver uses the navigation message sent from the GNSS satellites and tracks the pseudorange and Doppler raw observable measurements to provide a GNSS/INS system with the receiver's position, velocity, and time (PVT). This drift-free PVT solution is used to stabilize the solutions offered by the integrals of the accelerometer and gyroscope.

## System Fusion

Both the INS and GNSS can track the position and velocity of the system. An INS typically has reduced errors in the short-term, but larger, unbounded errors over extended periods of time. In contrast, GNSS tends to be noisier in the short-term, but has more stability over longer periods of time. When the two systems are integrated together, the GNSS measurements are able to regulate the INS errors and prevent their unbounded growth. An INS navigation solution also provides high output rates, while a GNSS navigation solution is typically only updated at rates between~1 Hz and~10 Hz. This allows the INS solution to bridge the gap between GNSS updates. A GNSS/INS system uses a Kalman filter to track an optimal estimate of the system's position, velocity, attitude, gyro bias, and accelerometer bias.

### High-Accuracy Pitch & Roll

Unlike the AHRS filter, no assumption regarding the accelerometer measuring only gravity is made. Pitch and roll are still determined by knowing the direction of gravity, but the GNSS measurements make it possible to account for the impact of dynamic motion on the accelerometer readings. Combined with the ability to track accelerometer bias, the dynamic accuracy of pitch and roll in a GNSS/INS system is typically 1-2 orders of magnitude better than that of an AHRS.

### Dynamic Alignment

Under sufficient dynamic motion, a GNSS/INS determines heading through a process known as dynamic alignment. The system correlates the acceleration measurements from the accelerometer with the position and velocity measurements from the GNSS receiver and is able to accurately derive the heading through this comparison. For example, consider an accelerometer that measures that a system is accelerating in the negative y-axis of the vehicle, while the GNSS reports the system is accelerating West, as shown in Figure 1.18. Correlating these two measurements together yields that the negative y-axis must be aligned to West, and so the system must be pointing North. Some systems -- primarily legacy systems -- require a specific pattern of motion to achieve dynamic alignment. But all that is required for most modern systems is horizontal acceleration of any type, such as accelerating down a runway at takeoff, driving around the block, or flying a figure-8. In fact, most smaller vehicles simply need to get up to a decent speed to trigger dynamic alignment; the small fluctuations of a car at highway speed or a Cessna in light turbulence is enough for the Kalman filter to observe heading. Note that the process of dynamic alignment is not the same as assuming heading is in the same direction as the velocity vector. It is a measure of the true heading of the vehicle, completely independent from course over ground (COG).

### Coupling Architecture

When combining a GNSS and INS system together, there are a few different integration architectures that can be used to couple the measurements from each of the two systems. These different approaches are commonly referred to as loosely-coupled, tightly-coupled, and ultra-tightly-coupled, and are shown in Figure 1.19.

## Challenges of GNSS/INS

While many of the limitations GNSS and INS face as standalone systems can be mitigated by combining them together, there are still a few challenges that come with using a GNSS-aided INS system, including losing the heading information in static or low dynamic situations, the fact that GNSS errors are non-Gaussian and non-zero mean, and the possibility of GNSS outages.

### Static or Low-Dynamic Situations

A GNSS/INS system loses observability of heading during low-dynamic or static situations, where dynamic alignment becomes impossible. During short duration periods of low dynamics, the INS can maintain an accurate, though continuously degrading, heading (on the order of 1 \minute for industrial grade). Most GNSS/INS systems fall back on an integrated magnetometer to continue stabilizing heading, though the issues with magnetic heading experienced in an AHRS system come into play.

### GNSS Errors

Another challenge a GNSS/INS system faces is that the nature of GNSS measurement errors are non-Gaussian and non-zero mean. Non-Gaussian errors have a distribution that does not resemble that of a bell-curve shape, while non-zero mean errors contain a distribution with a mean that is not equal to zero, similar to Figure 1.20. A critical assumption used to derive optimality of a Kalman filter is that any errors in the system are Gaussian and zero-mean. Since GNSS errors violate this assumption, extra care must be taken when tuning a GNSS/INS Kalman filter to achieve the best performance.

### GNSS Outages & Blockages

GNSS outages also pose a problem to a GNSS/INS system and can occur from a signal blockage or a signal interference. A GNSS signal blockage can be caused by anything from buildings to a tree that prevents the signal transmitted by the GNSS satellites from reaching the GNSS receiver, as illustrated in Figure 1.21. Signal interference is caused by a disturbance and can be intentional, such as in the case of jamming or spoofing, or unintentional, such as radio broadcasting signals that create disturbances on the signal. When GNSS outages occur, the GNSS/INS system defaults to an INS, which relies only on the IMU sensors to derive a navigation solution. Depending on the classification of the IMU sensors, using an INS alone to determine the navigation solution could lead to a large drift of the estimate over a short period of time.