Inertial Sensor DSP Engineer — Kalman & Embedded C++

Destinus; Hengelo; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

Destinus is seeking a Digital Signal Processing Engineer to own the control algorithms of a precision inertial sensor. You will define and tune loops, develop estimation and compensation methods, and validate performance using mathematical models and simulations.

The role focuses on Kalman filtering, bias estimation, thermal compensation, and state estimation, with strong emphasis on C/C++ for embedded targets and Python/MATLAB for analysis and validation.

Formación

• Strong background in control theory and DSP, including closed-loop design and stability margins.
• Experience with state estimation and Kalman filtering on real systems.
• Proficiency in Python or MATLAB for modeling, simulation, and analysis.

Responsabilidades

• Design and simulate control loops to keep the sensing element stable and locked; include frequency tracking (PLL).
• Define loop architectures, bandwidths, gains, and stability margins per sensor physics and requirements.
• Develop slower outer-loop algorithms for bias estimation and thermal compensation; implement in C/C++ for embedded targets.
• Design and implement Kalman filtering approaches to convert sensor output into accurate rate measurements.
• Own co-simulation environment to compare hardware vs reference models and identify discrepancies.
• Build mathematical and simulation models in Python or MATLAB to explore sensor behavior and validate designs.
• Establish and interpret sensor characterization methods including Allan variance, bias instability, and angular random walk.

Conocimientos

Control theory

Digital signal processing

Kalman filtering

C/C++ for embedded targets

Python or MATLAB

State estimation

Educación

B.Sc./M.Sc./PhD in CS / Applied Math / Engineering

Herramientas

Python

MATLAB

C/C++

Descripción del empleo

Destinus is seeking a Digital Signal Processing Engineer to own the control algorithms of a precision inertial sensor. You will define and tune loops, develop estimation and compensation methods, and validate performance using mathematical models and simulations.

The role focuses on Kalman filtering, bias estimation, thermal compensation, and state estimation, with strong emphasis on C/C++ for embedded targets and Python/MATLAB for analysis and validation.