An Innovative Asynchronous, Multi-rate, Multi-sensor State Vector Fusion Algorithm for Air Defence Applications

Shivanand, G; Reddy, K Vamshi Krishna; Prasad, D.B.N.

doi:10.1016/j.ifacol.2016.03.076

Cited by 9 publications

(5 citation statements)

References 2 publications

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“…G. Shivanand et al explored different algorithms for fusing asynchronous multi-rate multi-sensor data in real time, which is involved in air defence applications. [1] Y. Jiang et al used confidence distance theory and bayesian estimation in the fusion method of multi-sensor measurement data and considered the statistical characteristics of sensor output in the confidence distance theory, finding that it is more scientific to use the relation between the output data of each sensor to judge its validity. The study shows that the fusion of two kinds of technology, will give full play to the advantages of the technology.…”

Section: Related Workmentioning

confidence: 99%

The attitude control optimization of small rocket

Wen

Jia

et al. 2022

J. Phys.: Conf. Ser.

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In this article, an optimization method for attitude calculation and vector control of small rocket is proposed, which reduces the performance requirements and costs of gyroscopes. Dynamic model parameters such as engine thrust curve and rocket body moment of inertia are added to the traditional filtering and control algorithm, which can reduce the hardware performance requirements of sensors and the cost of rocket control system. This method has achieved good results in the test, and is of great significance for the promotion of small rockets.

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Section: Related Workmentioning

confidence: 99%

The attitude control optimization of small rocket

Wen

Jia

et al. 2022

J. Phys.: Conf. Ser.

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“…In recent years, several researchers have made efforts in different fields to study and improve multi-sensor data fusion methods and their fusion algorithms. Different algorithms for real-time fusion of asynchronous multilateral multi-sensor data, which involves air defense applications, were explored by G. Shivanand et al [5] Umair Ali et al found that current multi-sensor fusion algorithms have shortcomings in handling multi-sensor data. For example, the Kalman filter cannot handle non-Gaussian noise, while parametric filters such as Monte Carlo localization are computationally expensive.…”

Section: Related Workmentioning

confidence: 99%

Parachute control system of sounding rocket based on multi-sensor fusion

Wen

Li²,

Zhou³

et al. 2022

International Conference on Mechanisms and Robotics (ICMAR 2022)

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In this paper, a method for controlling the parachute opening device of a small sounding rocket through a multi-sensor fusion algorithm is proposed. This method uses IMU, airspeed tube and GNSS to obtain acceleration, velocity and position information respectively. After processing the three sets of data, the corresponding speed data is obtained, and the more accurate speed data is obtained through the Kalman filter algorithm. The vertical speed is used as the basis for the parachute-opening judgment condition and the timing of parachute-opening. Through simulation and experimental results, this method of parachute control of the sounding rocket proved to be very effective. This method can significantly reduce the accuracy requirements for the sounding rocket sensors, and obtain relatively high-precision results through the fusion processing of data collected by multiple low-precision sensors. This method can be used in the parachute control system of low-cost sounding rockets, which is of great significance for reducing the cost of small sounding rockets and promoting commercial applications.

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“…3 . These estimated states are then centrally fused using a weighted sum of the state estimates [10]. The fusion algorithm for state and covariance matrix are described as below.…”

Section: Multisensor Fusionmentioning

confidence: 99%

Stochastic Filtering Technique for UAV-Based Communications On The Move Terminal Tracking Accuracy Evaluation

Omi

Shin

Tsourdos

et al. 2021

2021 Antenna Measurement Techniques Association Symposium (AMTA)

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Along with the growth of communication and satellite industry, the importance of satellite antenna evaluation is increasing. Particularly Communication On The Move (COTM) terminal antenna, including the communication between new types of constellations on LEO and MEO, requires tracking accuracy test for the communication on moving vehicles. The conventional test facilities are locally fixed and lack flexibility. To make the antenna measurement more accessible, we are developing a methodology for in-situ measurement by introducing multiple Unmanned-Aerial-Vehicles (UAVs) system with RF payload. Thanks to the dynamic flexibility of UAVs, this system can flexibly change the test configuration on site and make new test scenarios available, such as emulating the orbit of non-GEO satellites during the measurement. However, one of the challenges of the proposed system is the additional uncertainties during the measurement due to the mobility of UAVs. To overcome this challenge, we design recursive stochastic filtering and fusion approaches, and evaluate their estimation performance via numerical simulations. By introducing stochastic filter and fusion algorithms, the effect of error is mitigated, and better accuracy can be achieved compared to an existing method. This project is performed in collaboration with Cranfield University in the UK and QuadSAT in Denmark.

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An Innovative Asynchronous, Multi-rate, Multi-sensor State Vector Fusion Algorithm for Air Defence Applications

Cited by 9 publications

References 2 publications

The attitude control optimization of small rocket

The attitude control optimization of small rocket

Parachute control system of sounding rocket based on multi-sensor fusion

Stochastic Filtering Technique for UAV-Based Communications On The Move Terminal Tracking Accuracy Evaluation

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