## 5 Conclusions  
The paper proposed a new redundant inertial attitude system, with a detection unit containing three gyro sensor clusters arranged in linear configurations. The direct application of the here proposed methodology is the estimation of small satellites' attitude-based gyro measurements, providing at the same time a high degree of redundancy of the inertial detection unit equipped with miniaturized sensors. The concept started from the idea that it would be less expensive and safer to replace the classical arrangement of the IMU sensors (rectangular triads of gyros) with multiple miniaturized gyros mounted on each of the three axes of the IMU (in linear detection clusters) to measure the same quantity and subsequently fuse their data. The developed data fusion method combined the outputs of these multiple sensors to estimate improved values for the components of the variables needed to calculate the satellite attitude in terms of roll, pitch, and yaw attitude angles by using inertial methods. The developed algorithm used a mechanism based on the maximal ratio combining the data fusion method involved in the processing of the signals in the telecommunications field. The integrated architecture of the redundant attitude-system-based inertial techniques included the following: (1) a 3D redundant gyro detection unit with twelve MEMS gyros, which were disposed in three clusters with four sensors in linear configuration in each of them, allowing the measurement of angular speeds along the body frame axes; (2) three data fusion blocks, one for each detection channel, implementing software the data fusion method; and (3) the attitude algorithm, implementing software the numerical signal processing flow used in the determination of attitude angles starting from the gyro data. First tested was the attitude algorithm; its numerical simulation analysis and the bench test results proved that the software model developed for the algorithm worked well, validating in this way its operation. The next tests for the attitude algorithm were based on experimental data provided by a gyro triad with MEMS sensors, equipping the inertial measurement unit of the SDINS/GPS navigator. As a reference for the developed attitude algorithm evaluation, we used the attitude component (roll, pitch and yaw angles) of the solution of navigation offered by the SDINS/GPS integrated navigator. The obtained results showed that the attitude solutions provided by the reference navigator and by the developed algorithm were very close. The next on the test list was the software model implementing the data fusion algorithm, which was also simulated and evaluated in various situations. A simple experimental test performed at the laboratory level was the use of four accelerometers in the cluster measurement, naturally excited by the local gravitational field in three situations, \(g_{horizontal}=0\) m/s\({}^{2}\), \(g_{vertical+}=9.80655\) m/s\({}^{2}\) and \(g_{vertical-}=-9.80655\) m/s\({}^{2}\), where the sensitivity axis of the cluster was directed horizontally, and along the local vertical, up and down. The obtained results show that the standard deviation of the fused signal decreased by 1.7720 times comparatively with sensor no. 2 (the best in the cluster), by 2.2661 times comparatively with sensor no. 3 (the worst in the cluster), and by 2.0266 times comparatively with the average of the mean dispersions for all sensors in the cluster, when its sensitivity axis was on the horizontal plane. In the other two testing cases, the obtained reductions for the mean standard deviation were as follows: (1) at 9.80655 m/s\({}^{2}\) excitation: 1.7694 times comparatively with sensor no. 2, 2.2565 times comparatively with the average of the mean dispersions; (2) at \(-9.80655\) m/s\({}^{2}\) excitation: 1.7564 comparatively with sensor no. 2, 2.3803 times comparatively with sensor no. 3, and 2.0140 times comparatively with the average of the mean dispersions.