• Journal of Positioning, Navigation, and Timing
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• 제13권2호
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• pp.137-147
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• 2024

This paper presents a novel Long Short-Term Memory (LSTM) network architecture for the integration of an Inertial Measurement Unit (IMU) and Global Navigation Satellite Systems (GNSS). The proposed algorithm consists of two independent LSTM networks and the LSTM networks are trained to predict attitudes and velocities from the sequence of IMU measurements and mechanization solutions. In this paper, three GNSS receivers are used to provide Real Time Kinematic (RTK) GNSS attitude and position information of a vehicle, and the information is used as a target output while training the network. The performance of the proposed method was evaluated with both experimental and simulation data using a lowcost IMU and three RTK-GNSS receivers. The test results showed that the proposed LSTM network could improve positioning accuracy by more than 90% compared to the position solutions obtained using a conventional Kalman filter based IMU/GNSS integration for more than 30 seconds of GNSS outages.

• Journal of Positioning, Navigation, and Timing
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• 제3권2호
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• pp.53-62
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• 2014

In the guided missile and unmanned vehicle system, the navigation system is one of the most important components. Recently, low-cost effective smart projectiles and guided bomb are being developed using MEMS based navigation system which has high-G, low-cost and small size. In this paper, locally developed MEMS based GPS/INS integrated navigation system will be introduced in comparison with the state of the art of MEMS based navigation system. And technical design and development method is described to satisfy the required performance of GPS receiver, MEMS inertial sensor assembly, navigation computer and software.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1589-1597
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• 2021

Due to the low output rate and time delay of vehicle's navigation results, the electro-optical tracking system(EOTS) cannot estimate accurate target positions. If an inertial measurement unit(IMU) is additionally mounted into the EOTS and inertial navigation system(INS) is constructed, the high navigation output rate can be obtained. And the time-delay can be compensated by using the augmented Kalman filter. An accurate initial attitude is required in order to have accurate navigation outputs. In this paper, an attitude determination algorithm is proposed using the augmented Kalman filter in order to compensate measurement delay of the EOTS and have accurate initial attitude. The proposed initial attitude determination algorithm consists of an augmented Kalman filter, an INS, and an integrated Kalman filter. The augmented Kalman filter compensates the time-delay of the vehicle's navigation results and the integrated Kalman filter estimates the navigation error of the INS. In order to evaluate performance of the proposed algorithm, vehicle's navigation outputs and IMU measurements were generated using sensors' model-based measurement generator and initial attitude estimation errors of the proposed algorithm and the conventional algorithm without the augmented Kalman filter were compared for the generated measurements. The evaluation results show that the proposed algorithm has better accuracy.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 추계학술대회
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• pp.41-46
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• 2004

본 논문에서는 속도 구속조건을 갖는 수중이동체를 초기위치로부터 목적위치에 접안하는 제어기법에 대해서 논의한다. 단, 수중이동 체는 일정방향으로 속도성분을 갖지 않는 즉, 속도구속조건을 가지는 것으로 가정한다. 본 논문에서는 이러한 시스템에 대하여 비 홀로노믹적인 관점에서 시스템을 해석하고 수중이동체를 체인드폼으로 변환한 후 Multi-rate 디지털 제어기법을 적용하여 자세제어를 행하고 수치시뮬레이션을 통하여 제어기법의 유용성을 평가하였다.

• International Journal of Aeronautical and Space Sciences
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• 제18권3호
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• pp.565-573
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• 2017

This paper presents a multistage in-flight alignment (MIFA) method for a strapdown inertial navigation system (SDINS) suitable for moving vehicles with no initial attitude references. A SDINS mounted on a moving vehicle frequently loses attitude information for many reasons, and it makes solving navigation equations impossible because the true motion is coupled with an undefined vehicle attitude. To determine the attitude in such a situation, MIFA consists of three stages: a coarse horizontal attitude, coarse heading, and fine attitude with adaptive Kalman navigation filter (AKNF) in order. In the coarse horizontal alignment, the pitch and roll are coarsely estimated from the second order damping loop with an input of acceleration differences between the SDINS and GPS. To enhance estimation accuracy, the acceleration is smoothed by a scalar filter to reflect the true dynamics of a vehicle, and the effects of the scalar filter gains are analyzed. Then the coarse heading is determined from the GPS tracking angle and yaw increment of the SDINS. The attitude from these two stages is fed back to the initial values of the AKNF. To reduce the estimated bias errors of inertial sensors, special emphasis is given to the timing synchronization effects for the measurement of AKNF. With various real flight tests using an UH60 helicopter, it is proved that MIFA provides a dramatic position error improvement compared to the conventional gyro compass alignment.

• 한국군사과학기술학회지
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• 제11권6호
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• pp.21-29
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• 2008

Korean army currently considers the development of the advanced MLRS(Multiple Launcher Rocket System) as a new alternative, which responses on the renovation of the artillery and future battle field environment. Therefore, This study suggests that the development methods of MLRS based on the analysis of the future battle field environment, world wide development trends of the MLRS and operation states of the domestic MLRS. According to this study, the development methods of new generation MLRS should be included a 230/130mm combined launcher competible with conventional 227mm on the vehicle, advanced FCS(Fire Control System), GPS/INS integration navigation system, Pod of ammunitiom, ammunition carrring vehicle and guided rocket munitions, etc.

• 제어로봇시스템학회논문지
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• 제14권1호
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• pp.27-35
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• 2008

A navigation system is one of the important components of an unmanned ground vehicle (UGV). A GPS receiver collects data signals transmitted by (Earth orbiting) satellites. However, these data signals may contain many errors resulting misinformation and depending on one's position (environment), reception may be impossible. The proposed self-driven algorithm uses three low-cost GPS in order to minimize errors of existing inexpensive single GPS's driving algorithm. By using reliable final data, which is analyzed and combined from each of three GPS's received data signals, gathering a vehicle's steering performance information and its current pin-point position is improved even with error containing signals or from a place where signal gathering is impossible. The purpose of this thesis is to explain navigation system algorithm using multiple GPS and compass sensor and prove the algorithm through experiments.

• Journal of Positioning, Navigation, and Timing
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• 제2권1호
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• pp.19-31
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• 2013

It is well known that the accident of vehicles carrying hazardous materials incurs huge losses economically and socially. To detect and respond rapidly against the accident of a vehicle carrying hazardous materials, it is essential to estimate the relative navigation information between the forward tractor module and the backward trailer module of the vehicle reliably and accurately. In this paper, a precise relative positioning system based on GPS is designed, implemented, and evaluated as a prerequisite to design an effective relative navigation system for the vehicle carrying hazardous materials. An experiment using field-collected 10 Hz real GPS measurements showed that the designed relative positioning system achieves 22 cm accuracy within 15 epochs by float solutions. Also, it was found that cm-level integer solutions can be generated reliably after the quick convergence of float solutions.

• 한국자동차공학회논문집
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• 제19권4호
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• pp.8-15
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• 2011

This paper proposes a real-time navigation algorithm which integrates the artificial potential field (APF) for an unmanned vehicle in the unknown environment. This approach uses repulsive potential function around the obstacles to force the vehicle away and an attractive potential function around the goal to attract the vehicle. In this research, laser range finder is used as range sensor. An obstacle detected by the sensor creates repulsive vector. Differential global positioning system (DGPS) and digital compass are used to measure the current vehicle position and orientation. The measured vehicle position is also used to create attractive vector. This paper proposes a new concept of potential field based navigation which controls unmanned vehicle's speed and steering. The magnitude of repulsive force based on the proposed algorithm is designed not to be over the magnitude of attractive force while the magnitude is increased linearly as being closer to obstacle. Consequently, the vehicle experiences a generalized force toward the negative gradient of the total potential. This force drives the vehicle downhill towards its goal configuration until the vehicle reaches minimum potential and it stops. The effectiveness of the proposed APF for unmanned vehicle is verified through simulation and experiment.

• 제어로봇시스템학회논문지
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• 제22권11호
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• pp.967-976
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• 2016

This paper presents a 3D carrier-smoothed GNSS/DR (Global Navigation Satellite System/Dead Reckoning) integrated system for precise ground-vehicle trajectory estimation. For precise DR navigation on sloping roads, the AHRS (Attitude Heading Reference System) methodology is employed. By combining the integrated carrier phase of GNSS and DR sensor measurements, a vehicle trajectory with an accuracy of less than 20cm is obtained even when cycle slip or change of visibility occur. In order to supplement the weak GNSS environment with DR successfully, the DR sensor is precisely compensated for using GNSS Doppler measurements when GNSS visibility is good. By integrating a multi-GNSS receiver with low-cost IMU, a precise 3D navigation system for land vehicles is proposed in this paper. For real-time implementation, a decoupled Kalman filter is employed in the integrated system. Through field experiments, the performance of the proposed system is verified in various road environments, including sloping roads, good-visibility areas, high multi-path areas, and under-ground parking areas.