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Kalman Filter Estimation Jobs in Alabama (NOW HIRING)

Leidos

Radar Analysis IPT Lead

Huntsville, AL · On-site

Evaluate tracking filter performance (e.g., Kalman-based estimators) * Assess dwell time, PRF selection, waveform tradeoffs, and coherent integration impacts * Identify algorithm sensitivities that ...

Leidos

Radar Analysis IPT Lead

Huntsville, AL · On-site

$87K - $157K/yr

Evaluate tracking filter performance (e.g., Kalman-based estimators) * Assess dwell time, PRF selection, waveform tradeoffs, and coherent integration impacts * Identify algorithm sensitivities that ...

Boeing

Senior Seeker Radar Systems Engineer

Huntsville, AL · On-site

$103K - $140K/yr

... Kalman filtering, probabilistic and statistical modeling, and measurement processing from pulsed ... estimation, filter design, resampling theory, etc.) * Experience with MATLAB for data analysis ...

Leidos

Radar Analysis IPT Lead

Huntsville, AL · On-site

Evaluate tracking filter performance (e.g., Kalman-based estimators) * Assess dwell time, PRF selection, waveform tradeoffs, and coherent integration impacts * Identify algorithm sensitivities that ...

Boeing

Senior Seeker Radar Systems Engineer

Huntsville, AL · On-site

$103K - $140K/yr

... Kalman filtering, probabilistic and statistical modeling, and measurement processing from pulsed ... estimation, filter design, resampling theory, etc.) * Experience with MATLAB for data analysis ...

Boeing

Senior Seeker Radar Systems Engineer

Huntsville, AL · On-site

$103K - $140K/yr

... Kalman filtering, probabilistic and statistical modeling, and measurement processing from pulsed ... estimation, filter design, resampling theory, etc.) * Experience with MATLAB for data analysis ...

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Kalman Filter Estimation information

What is Kalman filter estimation?

Kalman Filter Estimation is a mathematical algorithm used to estimate the state of a dynamic system from a series of noisy measurements. It is widely applied in fields such as robotics, aerospace, and navigation to provide real-time, optimal estimates of unknown variables by combining predictions from a model with observed data. The filter works recursively, meaning it updates its estimates and uncertainties as new measurements become available. Its strength lies in efficiently handling uncertainties and noise in both the system model and the measurements.

What are the key skills and qualifications needed to thrive as a Kalman filter estimation engineer, and why are they important?

To excel as a Kalman Filter Estimation Engineer, you need a strong background in control theory, linear algebra, statistics, and typically a degree in electrical engineering, robotics, or applied mathematics. Familiarity with MATLAB, Python, C++, and simulation tools like Simulink, as well as experience implementing Kalman filters in real-time systems, is highly valued. Analytical thinking, problem-solving, and effective communication are important soft skills for collaborating with multidisciplinary teams and presenting complex results. These competencies ensure accurate state estimation and system reliability in applications such as navigation, robotics, and sensor fusion.

What are some common challenges faced by professionals working in Kalman filter estimation, and how can they be addressed?

Professionals working in Kalman Filter Estimation often encounter challenges such as model inaccuracies, noisy sensor data, and computational limitations, especially in real-time applications. Addressing these issues typically involves rigorous sensor calibration, careful tuning of filter parameters, and choosing appropriate variants of the Kalman filter, such as the Extended or Unscented Kalman Filter for nonlinear systems. Collaboration with domain experts and regular validation against ground truth data also help ensure robust performance. Additionally, staying updated with the latest research and tools in estimation theory can provide innovative solutions to emerging challenges.

What is the difference between Kalman Filter Estimation vs Signal Processing Engineer?

AspectKalman Filter EstimationSignal Processing Engineer
CredentialsMathematics, control systems, engineering degreesElectrical engineering, computer science, or related fields
Work EnvironmentResearch labs, aerospace, robotics, automationCommunications, audio/video, telecommunications industries
Industry UsageNavigation, robotics, sensor fusionFiltering, data analysis, signal enhancement

Kalman Filter Estimation focuses on estimating the state of dynamic systems using mathematical models, often in robotics and navigation. Signal Processing Engineers design and implement algorithms to analyze and modify signals in various industries. While both roles involve data analysis and mathematical skills, Kalman Filter Estimation is specialized in state estimation for control systems, whereas Signal Processing Engineers work broadly on signal manipulation and enhancement.

What are popular job titles related to Kalman Filter Estimation jobs in Alabama?

For Kalman Filter Estimation jobs in Alabama, the most frequently searched job titles are:

What job categories do people searching Kalman Filter Estimation jobs in Alabama look for?

The top searched job categories for Kalman Filter Estimation jobs in Alabama are:

Kalman Filter Estimation jobs near you

Guidance, Navigation, and Control (GNC) Engin

Huntsville, AL • On-site

Synovix, Inc.
See more jobs at Synovix, Inc.external

Full-time

Posted 17 days ago

Job description

Job Title: Guidance, Navigation, and Control (GNC) EngineerPosition Overview

Synovix is seeking two experienced Guidance, Navigation, and Control Engineers to support an on-site missile and weapon systems program for a defense customer in Northridge, California. The engineers will develop and assess guidance, navigation, control, estimation, and sensor-fusion solutions from early analysis through integration and test. 

What You Will Do
  • Develop, analyze, and mature guidance, navigation, control, estimation, and sensor-fusion algorithms for missile and weapon system applications.
  • Design and tune Kalman filter-based estimators, including extended or unscented approaches where appropriate to the solution.
  • Develop and evaluate flight dynamics, navigation error models, autopilot functions, guidance laws, and control-system performance.
  • Use MATLAB and Simulink for trade studies, sensitivity analyses, Monte Carlo assessments, and requirements verification. Integrate algorithms with six-degree-of-freedom and hardware-in-the-loop environments.
  • Analyze system performance, document recommendations, and support technical reviews; establish GNC architecture, lead trades, mentor engineers, and coordinate across systems, software, algorithms, modeling, hardware, and test teams.
Required Qualifications
  • At least 8 years of relevant GNC, estimation, controls, navigation, or flight dynamics experience.
  • Bachelor's degree in aerospace engineering, mechanical engineering, electrical engineering, applied mathematics, physics, or a closely related technical discipline.
  • Strong foundation in dynamics, control theory, state estimation, numerical methods, and linear algebra.
  • Hands-on experience developing and evaluating algorithms in MATLAB and/or Simulink.
  • Experience analyzing time-domain and frequency-domain performance and communicating conclusions through technical documentation and reviews.
  • Ability to work full-time on site in Northridge, California.
  • U.S. citizenship and eligibility to obtain a U.S. government security clearance if required by the program; an active clearance is not required at hire.
Preferred Qualifications
  • Direct missile, interceptor, guided weapon, flight control, or aerospace GNC experience.
  • Experience with Kalman filtering, inertial navigation, GPS-aided navigation, sensor fusion, target-state estimation, or tracking.
  • Experience with six-degree-of-freedom simulation, Monte Carlo analysis, flight envelopes, and performance requirements allocation.
  • Working knowledge of C/C++, Python, embedded implementation, or automatic code-generation workflows.
  • Experience integrating radar, electro-optical/infrared, inertial, GPS, or other sensor data into a navigation or guidance solution.
  • Experience supporting software-in-the-loop, hardware-in-the-loop, ground test, flight test, or post-test data analysis.

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