Digital Signal Processing: Laboratory Experiments Using C and the TMS320C31 DSK

Chassaing, Rulph

doi:10.1002/0471200654

Cited by 31 publications

(29 citation statements)

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“…As shown in Figure 4, the main parameter of this filter is the v 1 parameter. It consists of a number between 0 and 1 stating how much signal is allowed to pass as output signal [2].…”

Section: Filter Characteristicsmentioning

confidence: 99%

“…The main objectives of the experiment are: (1) To test a collection of filters required for inertial navigation systems in an ordered configuration according to their executions; (2) To determine the individual parameter of each filter aiming at real time results; (3) To implement the Kalman filter, low pass filter, high-pass filter, moving average filter, and median filter for signal filtering; and (4) To generate real time graphical results associated with the output obtained from the experiment.…”

Section: Introductionmentioning

confidence: 99%

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Experiment on signal filter combinations for the analysis of information from inertial measurement units in AOCS

Pontuschka

Fonseca²,

Melo

2015

J. Phys.: Conf. Ser.

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Abstract. The FDIR software subsystem may be part of the attitude and orbit control subsystem, AOCS. The AOCS quite often includes inertial navigation sensors being physically implemented by accelerometers and gyroscopes which provide electrical signals to the AOCS on-board software (OBSW) which, in its turn, generates the commands to the control actuators. In general, hardware like sensors and actuators present nonlinearities which sometimes make it difficult to properly interpret the output signals. In the scenario of space applications, filters are used to eliminate noise and to increase the reliability for the correct interpretation of those signals. In this paper we present a collection of filters used in inertial navigation subsystems enabling the fusion of data from sensors. Fundamentally, the filters are composed of the Kalman filter in its derivations. The filters can be used for state estimation of a system as well as for noise filtering. In this work the filters are configured with respect to their different orders of execution, their sampling rate, and their cutting-off frequency. The filter configurations can be changed by software so as to allow a flexible structure that can be adjusted for the best quality of output signal and consequently the best analysis of the satellite behaviour. The main purpose of this paper is to test the algorithm that combines several signal filters considered in this study. To accomplish this goal we developed an experiment encompassing an accelerometer and a wireless communication system so as to provide input signals to be filtered by the filtering algorithm.

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“…As shown in Figure 4, the main parameter of this filter is the v 1 parameter. It consists of a number between 0 and 1 stating how much signal is allowed to pass as output signal [2].…”

Section: Filter Characteristicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experiment on signal filter combinations for the analysis of information from inertial measurement units in AOCS

Pontuschka

Fonseca²,

Melo

2015

J. Phys.: Conf. Ser.

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“…The servo motion controller used the Texas Instruments (TI) TMS 320 C31 DSP processor [2,[13][14]; the image acquisition used the National Instruments (NI) IMAQ 1409 image grab card [16]; and the software programs of image recognition, space coordination calculation, fuzzy logic implementation, robot host controller were developed using the Microsoft Visual C++ [8]. The hardware and software components were properly integrated to achieve the desired purposes.…”

Section: Biomedical Engineering-applications Basis and Communicationsmentioning

confidence: 99%

Development of a Surgical Navigation Robot Using Image Servo Tracking Techniques

Chen

Tsai

Huang

et al. 2004

Biomed. Eng. Appl. Basis Commun.

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This paper presents the development of surgical navigation robot, which is designed based on the image servo tracking technique. The surgical navigation robot plays an important role to the computer aided surgery (CAS), since it provides the patient's space coordinate during surgical navigation stage in real-time. Especially, the proposed active image servo tracking based surgical navigation robot can track the surgical marker that is mounted on the patient's hard tissue of the surgical position, so that the navigation space can be automatically extended. The proposed surgical navigation robot system consists of the in-lab designed dual-axis eye-in-hand robot (EIHR), digital signal processor (DSP) based EIHR motion controller, image servo tracking and positioning software. The EIHR robot is composed of the dual-axis robot mechanics and two CCD cameras, which acts as the stereoscopic image capture platform. The DSP based EIHR motion controller is designed to control the EIHR robot in a desired velocity, so that the surgical marker can be dynamically tracked. The image servo tracking and positioning software is the kernel of this work, and it is composed of image capture and recognition module, fuzzy logic based surgical marker tracking module and surgical marker positioning module. The image capture and recognition module is developed to abstract the image features of the surgical marker. The intelligent fuzzy logic based surgical marker tracking module is capable of generating robot's control command so that the surgical marker can be tracked within the desired target window. In addition, the surgical marker positioning module is used to calculate the surgical marker's space coordinates in terms of the features of stereoscopic images and the robot's posture. Finally, the prototype had been finished, and the experiment results showed that proposed EIHR achieved 1.7 mm position error within 500 mm operation range.

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“…in 1998 and became its subsidiary), 3. the platform is well supported by many demonstration code examples and from the point of view of the teacher, a significant help is provided by the T.I. C31 Teaching Kit [2] that is based on the same platform, as well as by existing literature dedicated to the topic of C31 based laboratory experiments [3,4].…”

Section: Rationale Methodology and Structurementioning

confidence: 99%

“…plements a 6th order band-pass filter suggested in [3], using a type 2 direct realization structure. This same filter is also illustrated in a Matlab command file that is also provided.…”

Section: Iir Filtering An Assembly Code Is Provided That Im-mentioning

confidence: 99%

Grasping the potential of digital signal processing through real-time DSP laboratory experiments

Ferreira

Restivo²

Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, 2002 and the 2nd Signal Processing Education Workshop.

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A new DSP laboratory course has been included in the Electrical and Computer Engineering curriculum at the Faculdade de Engenharia da Universidade do Porto, in Portugal, since the school year of 1999/2000. This paper addresses the context and motivation underlying this new course, outlines its structure and methodology, highlights the design and goals of all DSP experiments currently proposed for the 13 weeks of the semester, and reports on the receptivity students have expressed to this elective course. The course is based on the TI C31 Starter Kit and tries to combine full use of its resources with a representative diversity of efficient digital signal processing techniques and associated application scenarios. A perspective is also given on current plans to reinforce DSP expertise at the graduate level.

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Digital Signal Processing: Laboratory Experiments Using C and the TMS320C31 DSK

Cited by 31 publications

References 0 publications

Experiment on signal filter combinations for the analysis of information from inertial measurement units in AOCS

Experiment on signal filter combinations for the analysis of information from inertial measurement units in AOCS

Development of a Surgical Navigation Robot Using Image Servo Tracking Techniques

Grasping the potential of digital signal processing through real-time DSP laboratory experiments

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