GPS-Free Terrain-Based Vehicle Tracking Performance as a Function of Inertial Sensor Characteristics

2011 ◽  
Author(s):  
Kshitij Jerath ◽  
Sean N. Brennan
Keyword(s):  
Kalman Filters ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Tracking Error ◽  
Vehicle Tracking ◽  
Tracking Performance ◽  
Tracking Accuracy ◽  
Localization Algorithms ◽  
Bias Instability

Prior experiments have confirmed that specific terrain-based localization algorithms, designed to work in GPS-free or degraded-GPS environments, achieve vehicle tracking with tactical-grade inertial sensors. However, the vehicle tracking performance of these algorithms using low-cost inertial sensors with inferior specifications has not been verified. The included work identifies, through simulations, the effect of inertial sensor characteristics on vehicle tracking accuracy when using a specific terrain-based tracking algorithm based on Unscented Kalman Filters. Results indicate that vehicle tracking is achievable even when low-cost inertial sensors with inferior specifications are used. However, the precision of vehicle tracking decreases approximately linearly as bias instability and angle random walk coefficients increase. The results also indicate that as sensor cost increases, the variance in vehicle tracking error asymptotically tends to zero. Put simply, as desired precision increases, increasingly larger and quantifiable investment is required to attain an improvement in vehicle tracking precision.

A rapid seismic data calibration technique using integrated micro-electro-mechanical system inertial sensor groups for a 3C vertical seismic profile

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. P109-P118
Author(s):  
Huailiang Li ◽  
Xianguo Tuo ◽  
Tong Shen ◽  
Mark Julian Henderson ◽  
Jérémie Courtois
Keyword(s):  
Mechanical System ◽  
Seismic Data ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Measuring Method ◽  
Seismic Profile ◽  
Micro Electro Mechanical System ◽  
Vertical Seismic Profile ◽  
Sensor Package

Calibration of 3C vertical seismic profile (VSP) data is an exciting challenge because the orientation of the tool is random when only seismic data are considered. We have augmented the sensor package on the VSP tool with micro-electro-mechanical system (MEMS) inertial sensors and applied a gesture measuring method to determine the tool orientation and calibration. This technique can quickly produce high precision, orientation, and angle information when integrated with the seismometer. The augmented sensor package consists of a low-cost triaxial MEMS gyroscope, an electronic compass, and an accelerometer. The technique to process the gesture information is based on the OpenGL software for 3D modeling. We have tested this approach on a large number of field data sets and it appeared to be faster and more reliable than other approaches.

scholarly journals Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2660 ◽  
Author(s):  
Fabio Alexander Storm ◽  
Ambra Cesareo ◽  
Gianluigi Reni ◽  
Emilia Biffi
Keyword(s):  
Inertial Sensors ◽  
Inertial Sensor ◽  
Pathological Condition ◽  
Low Cost ◽  
Walk Test ◽  
Female Ratio ◽  
Number Of Patients ◽  
Wearable Inertial Sensors ◽  
6 Minute Walk Test ◽  
Minute Walk

Wearable sensors are becoming increasingly popular for complementing classical clinical assessments of gait deficits. The aim of this review is to examine the existing knowledge by systematically reviewing a large number of papers focusing on the use of wearable inertial sensors for the assessment of gait during the 6-minute walk test (6MWT), a widely recognized, simple, non-invasive, low-cost and reproducible exercise test. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 28 full-text articles. Then, the available knowledge was summarized regarding study design, subjects enrolled (number of patients and pathological condition, if any, age, male/female ratio), sensor characteristics (type, number, sampling frequency, range) and body placement, 6MWT protocol and extracted parameters. Results were critically discussed to suggest future directions for the use of inertial sensor devices in the clinics.

Wireless Input Technology Based on MEMS Inertial Measurement Unit - A Survey

2017 ◽  
Vol 870 ◽  
pp. 79-84
Author(s):  
Zhen Xian Fu ◽  
Guang Ying Zhang ◽  
Yu Rong Lin ◽  
Yang Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Propagation Model ◽  
Measurement Unit ◽  
Input Device ◽  
Operational Environment ◽  
Inertial Measurement ◽  
Mems Imu

Rapid progress in Micro-Electromechanical System (MEMS) technique is making inertial sensors increasingly miniaturized, enabling it to be widely applied in people’s everyday life. Recent years, research and development of wireless input device based on MEMS inertial measurement unit (IMU) is receiving more and more attention. In this paper, a survey is made of the recent research on inertial pens based on MEMS-IMU. First, the advantage of IMU-based input is discussed, with comparison with other types of input systems. Then, based on the operation of an inertial pen, which can be roughly divided into four stages: motion sensing, error containment, feature extraction and recognition, various approaches employed to address the challenges facing each stage are introduced. Finally, while discussing the future prospect of the IMU-based input systems, it is suggested that the methods of autonomous and portable calibration of inertial sensor errors be further explored. The low-cost feature of an inertial pen makes it desirable that its calibration be carried out independently, rapidly, and portably. Meanwhile, some unique features of the operational environment of an inertial pen make it possible to simplify its error propagation model and expedite its calibration, making the technique more practically viable.

scholarly journals Performance Analysis of Adaptive Neuro Fuzzy Inference System Control for MEMS Navigation System

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ling Zhang ◽  
Jianye Liu ◽  
Jizhou Lai ◽  
Zhi Xiong
Keyword(s):  
Fuzzy Control ◽  
High Precision ◽  
Navigation System ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Inference System ◽  
Neuro Fuzzy

Characterized by small volume, low cost, and low power, MEMS inertial sensors are widely concerned and applied in navigation research, environmental monitoring, military, and so on. Notably in indoor and pedestrian navigation, its easily portable feature seems particularly indispensable and important. However, MEMS inertial sensor has inborn low precision and is impressionable and sometimes goes against accurate navigation or even becomes seriously unstable when working for a period of time and the initial alignment and calibration are invalid. A thought of adaptive neuro fuzzy inference system (ANFIS) is relied on, and an assistive control modulated method is presented in this paper, which is newly designed to improve the inertial sensor performance by black box control and inference. The repeatability and long-time tendency of the MEMS sensors are tested and analyzed by ALLAN method. The parameters of ANFIS models are trained using reasonable fuzzy control strategy, with high-precision navigation system for reference as well as MEMS sensor property. The MEMS error nonlinearity is measured and modulated through the peculiarity of the fuzzy control convergence, to enhance the MEMS function and the whole MEMS system property. Performance of the proposed model has been experimentally verified using low-cost MEMS inertial sensors, and the MEMS output error is well compensated. The test results indicate that ANFIS system trained by high-precision navigation system can efficiently provide corrections to MEMS output and meet the requirement on navigation performance.

Compensation for Stochastic Error of Gyros in a Dual-axis Rotational Inertial Navigation System

2015 ◽  
Vol 69 (1) ◽  
pp. 169-182 ◽  
Author(s):  
Zhichao Zheng ◽  
Songlai Han ◽  
Jin Yue ◽  
Linglong Yuan
Keyword(s):  
Navigation System ◽  
High Performance ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Inertial Navigation ◽  
Field Tests ◽  
Stochastic Error ◽  
Stochastic Errors

A dual-axis rotational Inertial Navigation System (INS) has received wide attention in recent years because of high performance and low cost. However, some errors of inertial sensors such as stochastic errors are not averaged out automatically during navigation. Therefore a Twice Position-fix Reset (TPR) method is provided to enhance accuracy of a dual-axis rotational INS by compensating stochastic errors. According to characteristics of an azimuth error introduced by stochastic errors of an inertial sensor in the dual-axis rotational INS, both an azimuth error and a radial-position error are much better corrected by the TPR method based on an optimised error propagation equation. As a result, accuracy of the dual-axis rotational INS is prominently enhanced by the TPR method, as is verified by simulations and field tests.

scholarly journals Validation of a Low-Cost Pavement Monitoring Inertial-Based System for Urban Road Networks

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3127
Author(s):  
Giuseppe Loprencipe ◽  
Flavio Guilherme Vaz de Almeida Filho ◽  
Rafael Henrique de Oliveira ◽  
Salvatore Bruno
Keyword(s):  
High Performance ◽  
Ride Comfort ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Road Networks ◽  
Measurement Unit ◽  
Raspberry Pi ◽  
Urban Road ◽  
Comfort Index

Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system (GPS) module, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to indirectly monitor the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO 2631 standard was used. Considering 21 km of roads with different levels of pavement decay, validation measurements were performed using the novel sensor, a high performance inertial based navigation sensor, and a road surface profiler. Therefore, comparisons between awz determined with accelerations measured on the two different inertial sensors are made; in addition, also correlations between awz, and typical pavement indicators such as international roughness index, and ride number were also performed. The results showed very good correlations between the awz values calculated with the two inertial devices (R2 = 0.98). In addition, the correlations between awz values and the typical pavement indices showed promising results (R2 = 0.83–0.90). The proposed sensor may be assumed as a reliable and easy-to-install method to assess the pavement conditions in urban road networks, since the use of traditional systems is difficult and/or expensive.

Sensitivity Comparison to Loop Latencies Between Damping Versus Stiffness Feedback Control Action in Distributed Controllers

2014 ◽  
Author(s):  
Ye Zhao ◽  
Nicholas Paine ◽  
Luis Sentis
Keyword(s):  
Closed Loop ◽  
Impedance Control ◽  
Tracking Error ◽  
Loop System ◽  
Tracking Performance ◽  
System Stability ◽  
Step Response ◽  
Tracking Accuracy ◽  
Closed Loop System ◽  
And Performance

This paper studies the effects of damping and stiffness feedback loop latencies on closed-loop system stability and performance. Phase margin stability analysis, step response performance and tracking accuracy are respectively simulated for a rigid actuator with impedance control. Both system stability and tracking performance are more sensitive to damping feedback than stiffness feedback latencies. Several comparative tests are simulated and experimentally implemented on a real-world actuator to verify our conclusion. This discrepancy in sensitivity motivates the necessity of implementing embedded damping, in which damping feedback is implemented locally at the low level joint controller. A direct benefit of this distributed impedance control strategy is the enhancement of closed-loop system stability. Using this strategy, feedback effort and thus closed-loop actuator impedance may be increased beyond the levels possible for a monolithic impedance controller. High impedance is desirable to minimize tracking error in the presence of disturbances. Specially, trajectory tracking accuracy is tested by a fast swing and a slow stance motion of a knee joint emulating NASA-JSC’s Valkyrie legged robot. When damping latencies are lowered beyond stiffness latencies, gravitational disturbance is rejected, thus demonstrating the accurate tracking performance enabled by a distributed impedance controller.

scholarly journals Performance Enhancement of Consumer-Grade MEMS Sensors through Geometrical Redundancy

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4851
Author(s):  
Giorgio de Alteriis ◽  
Domenico Accardo ◽  
Claudia Conte ◽  
Rosario Schiano Lo Moriello
Keyword(s):  
Random Walk ◽  
Performance Enhancement ◽  
Inertial Sensors ◽  
Low Cost ◽  
Cost Effective ◽  
Measurement Procedure ◽  
Measurement Unit ◽  
Mems Sensors ◽  
Mems Technology ◽  
Bias Instability

The paper deals with performance enhancement of low-cost, consumer-grade inertial sensors realized by means of Micro Electro-Mechanical Systems (MEMS) technology. Focusing their attention on the reduction of bias instability and random walk-driven drift of cost-effective MEMS accelerometers and gyroscopes, the authors hereinafter propose a suitable method, based on a redundant configuration and complemented with a proper measurement procedure, to improve the performance of low-cost, consumer-grade MEMS sensors. The performance of the method is assessed by means of an adequate prototype and compared with that assured by a commercial, expensive, tactical-grade MEMS inertial measurement unit, taken as reference. Obtained results highlight the promising reliability and efficacy of the method in estimating position, velocity, and attitude of vehicles; in particular, bias instability and random walk reduction greater than 25% is, in fact, experienced. Moreover, differences as low as 0.025 rad and 0.89 m are obtained when comparing position and attitude estimates provided by the prototype and those granted by the tactical-grade MEMS IMU.

scholarly journals Low-Cost MEMS-Based NARX Model for GPS-Denied Areas

2020 ◽  
pp. 58-70
Keyword(s):  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Autonomous Vehicle ◽  
Field Tests ◽  
Micro Electro Mechanical System ◽  
Integrated System ◽  
Main Challenge ◽  
Autonomous Vehicle Navigation ◽  
Narx Model

Autonomous vehicle navigation has witnessed a huge revolutionary revision regarding development in Micro-Electro Mechanical System (MEMS) technology. Most recently, Strapdown Inertial Navigation System (SDINS) has successfully been integrated with Global Positioning System (GPS). However, different grades of MEMS inertial sensors are available and choosing the convenient grade is quite important. Noises in inertial sensor are mostly treated through de-noising the additive errors to improve the precision of SDINS output. Unfortunately, integration in SDINS mechanization causes a growing in SDINS error output which considered the main challenge in integrating MEMS inertial sensors with GPS. This paper aims to promote the long-term performance of the MEMS-SDINS/GPS integrated system. A new integrated structure is proposed to model the nonlinearities that exist in SDINS dynamics in addition to the error uncertainty in the inertial sensors’ measurements. A robust Nonlinear AutoRegressive models with eXogenous inputs (NARX) based algorithm are designed for data fusion in the proposed GPS/INS integrated system. Validation for the proposed integrated system has been carried out using different field tests data in order to assess the accuracy of the system during GPS denied environment. The results obtained demonstrate that the proposed NARX model is applicative and satisfactory which shows a desired prediction performance.

scholarly journals Fusing Stereo Camera and Low-Cost Inertial Measurement Unit for Autonomous Navigation in a Tightly-Coupled Approach

2014 ◽  
Vol 68 (3) ◽  
pp. 434-452 ◽  
Author(s):  
Zhiwen Xian ◽  
Xiaoping Hu ◽  
Junxiang Lian
Keyword(s):  
Autonomous Navigation ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Three Dimensional ◽  
Fast Response ◽  
Location Estimation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Stereo Camera

Exact motion estimation is a major task in autonomous navigation. The integration of Inertial Navigation Systems (INS) and the Global Positioning System (GPS) can provide accurate location estimation, but cannot be used in a GPS denied environment. In this paper, we present a tight approach to integrate a stereo camera and low-cost inertial sensor. This approach takes advantage of the inertial sensor's fast response and visual sensor's slow drift. In contrast to previous approaches, features both near and far from the camera are simultaneously taken into consideration in the visual-inertial approach. The near features are parameterised in three dimensional (3D) Cartesian points which provide range and heading information, whereas the far features are initialised in Inverse Depth (ID) points which provide bearing information. In addition, the inertial sensor biases and a stationary alignment are taken into account. The algorithm employs an Iterative Extended Kalman Filter (IEKF) to estimate the motion of the system, the biases of the inertial sensors and the tracked features over time. An outdoor experiment is presented to validate the proposed algorithm and its accuracy.

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