Instantaneous ego-motion estimation using multiple Doppler radars

Kellner, Dominik; Barjenbruch, Michael; Klappstein, Jens; Dickmann, Jürgen; Dietmayer, Klaus

doi:10.1109/icra.2014.6907064

Cited by 95 publications

(28 citation statements)

References 11 publications

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“…Kellner et al [10]'s seminal work on radar odometry proposes a least-squares solution to recover the radar sensor's velocity from multiple target measurements, and leverages the Ackermann steering model to estimate the vehicle's velocity. Kellner et al [11] extend their work to multiple synchronous radar sensors. We note that our work neither makes any assumption of the vehicle model nor requires multiple radar sensors to be synchronous.…”

Section: Related Workmentioning

confidence: 99%

“…Discrete-time radar odometry methods typically make use of a single radar sensor for state estimation due to the asynchronous nature of the radar sensor. In instances involving the use of multiple radars [11], they have to be synchronised with one another. Discrete-time radar-inertial odometry methods require radar scans to have corresponding IMU measurements.…”

Section: A Continuous-time Trajectory Representationmentioning

confidence: 99%

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Continuous-time Radar-inertial Odometry for Automotive Radars

Ng¹,

Choi²,

Tan³

et al. 2022

Preprint

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We present an approach for radar-inertial odometry which uses a continuous-time framework to fuse measurements from multiple automotive radars and an inertial measurement unit (IMU). Adverse weather conditions do not have a significant impact on the operating performance of radar sensors unlike that of camera and LiDAR sensors. Radar's robustness in such conditions and the increasing prevalence of radars on passenger vehicles motivate us to look at the use of radar for ego-motion estimation. A continuous-time trajectory representation is applied not only as a framework to enable heterogeneous and asynchronous multi-sensor fusion, but also, to facilitate efficient optimization by being able to compute poses and their derivatives in closed-form and at any given time along the trajectory. We compare our continuous-time estimates to those from a discrete-time radar-inertial odometry approach and show that our continuous-time method outperforms the discrete-time method. To the best of our knowledge, this is the first time a continuous-time framework has been applied to radar-inertial odometry.

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Section: Related Workmentioning

confidence: 99%

Section: A Continuous-time Trajectory Representationmentioning

confidence: 99%

Continuous-time Radar-inertial Odometry for Automotive Radars

Ng¹,

Choi²,

Tan³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In [69] a Doppler-based approach to estimate the full 2D motion state of a vehicle is presented. It makes use of the fact that a vehicle is usually surrounded by numerous stationary targets which can be taken to first estimate the relative velocity vector between each sensor and target.…”

Section: B Speed-over-ground Estimationmentioning

confidence: 99%

Micrometer Sensing With Microwaves: Precise Radar Systems for Innovative Measurement Applications

et al. 2021

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Radar sensors have been widely used to estimate speed and displacement of remote targets. A novel market for contactless radar sensing is emerging in the field of automatization and process analysis, where non destructive testing and evaluation methods are desired. Here, modern radar systems offer various advantages over conventional sensors since they enable the contactless, continuous, and cost-efficient measurement of static or dynamic ranges. These can further be used for vibration and vital sign characterization. Advances in microwave technology, an increasing integration density, and the development of novel algorithms keep boosting the performance of the systems. After introducing the most common operation principles, such as unmodulated and frequency-modulated continuous-wave radar, different design aspects and building blocks of cutting-edge systems are explained in detail. In the second part, selected applications are described in detail. These include the sheet thickness monitoring of metallic foils, and the measurement of the ground speed of vehicles with the latest approaches. Exemplary low-power radar systems are presented to show the limits in terms of power consumption while still offering a high measurement precision. In addition, the topics of mechanical vibration sensing and vital sign sensing are addressed by introducing tailored systems.INDEX TERMS Radar theory, radar remote sensing, Doppler radar, radar applications.

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“…For self localisation the precise knowledge of the own motion and position, also called ego motion and position, is important. The motion and position can be determined using radar sensors [22,23] more robustly and with fewer errors during highly dynamic manoeuvres compared to standard vehicle odometry [2]. Additionally, landmarks are often used for self localisation [2,24] by recognising prominent, strongly reflective objects in the environment.…”

Section: Self Localisation: Ego Motion and Position Estimation Using mentioning

confidence: 99%