Kohlleppel, Robert: Ground moving target tracking with space-time adaptive radarBodenzielverfolgung mit Raum-Zeit adaptiver Signalverarbeitung. 2014
Inhalt
- Zusammenfassung
- Abstract
- Contents
- 1. Introduction
- 2. Fundamentals of ground moving target indication
- 2.1 Airborne MTI radar
- 2.2 The radar signal
- 2.3 Data processing and target detection
- 2.4 Signal model
- 2.5 Space time adaptive processing
- 3. Ground moving target indication and geolocation
- 3.1 Application of space time adaptive processing to a received data set
- Signal model of the received data set
- Data preprocessing
- Target detection with adjacent bin post Doppler processing
- 3.2 Parameter estimation
- 3.3 Geolocation of detections
- 4. Fundamentals of target tracking
- 4.1 Probability Hypothesis Density Filter
- 4.2 Gaussian Mixture Probability Hypothesis Density Filter
- 5. Ground moving target tracking algorithm
- 5.1 Basic design choices
- 5.2 Modifications of the standard GM-PHD filter
- State dependent detection probability
- Association between detections and components
- Merging with the Kullback-Leibler divergence
- Ancestor relation
- Immediate deletion of missed detection birth component descendants
- Component fingerprints
- Visualization of the GM-PHD filter results
- Track extraction
- 5.3 Ground moving target tracking specific adaptations of the GM-PHD
- Definition of the target state space
- State propagation
- Definition of the measurement space
- Definition of the observation process
- Jacobians of the observation process
- Modeling of the state dependent probability of detection
- An expression for the false alarm probability
- 5.4 Use of a digital elevation model
- 6. Tracking results with simulated data
- 6.1 Simulation of ground moving target detections by an airborne radar
- 6.2 Tracking results with simulated scenarios
- 6.3 Example of the direct visualization of GM-PHD filter results
- 6.4 Summary
- 7. Experimental results
- 8. Tracking with signal adaptive measurement error covariance matrix
- 8.1 Proposed model for the direction of arrival measurement error
- 8.2 Experimental validation of the direction of arrival measurment error model
- Association between detections and ground reference vehicles
- Deviation of the radar and GPS based DOA measurements
- Variance of the deviation between the DOA estimates
- Experimental results
- 8.3 Tracking with measurement covariance matrix adaptation
- 8.4 Simulation results
- 8.5 Tracking results with experimental data
- 9. Conclusion
- A. Algorithms
- A.1 Geolocation of a target
- Function for the geolocation based on target range and directional cosine
- Jacobian of the geolocation function
- Function for selecting one solution of the possible target geolocations
- Function for a unique solution for the geolocation of the target
- A.2 Measurable velocity component
- Function for the measurable velocity component of a target constrained to a plane
- Jacobian of the meausurable velocity with respect to the ENU parameters
- Determine a unique solution for the surface velocity component: bold0mu mumu ffdottedffffv urv
- A3. Range, radial velocity and directional cosine of a target
- A.4 Clutter Doppler frequency versus range and directional cosine
- A.5 Functions that are used by the tracking algorithm
- Radar measurement to track measurement conversion: bold0mu mumu ffdottedffffM urv
- Definition of the measurement function: bold0mu mumu hhdottedhhhhk
- Track measurement based on target state including measurement errors: bold0mu mumu ffdottedffffMS
- Track measurement based on the track state without effect of measurement noise: bold0mu mumu ffdottedffff0MS
- Conversion of a location from 2 to 3 dimensions: bold0mu mumu ffdottedffffp3 2
- Conversion of a velocity vector from 2 to 3 dimensions: bold0mu mumu ffdottedffffv3 2
- Conversion of a 3d location to 2 dimensions: bold0mu mumu ffdottedffff2 3
- Conversion of a 3d velocity vector to 2 dimensions bold0mu mumu ffdottedffffP2 E
- Locate a target in the tracking plane based on range and DOA measurement
- Radar measurements based on track state: bold0mu mumu ffdottedffffurvS
- Radar measurement based on track measurement: bold0mu mumu ffdottedffffurvM
- A.6 Jacobians of functions that are used by the tracking algorithm
- Jacobian of the functions that converts a 3d location to a 2d location
- Jacobian of the function that converts the range Doppler measurement to a location in the tracking plane
- Jacobian of the function that converts the radar measurment to the track input measurement
- Jacobian of the track measurement with respect to measurement noise
- Jacobian of the synthetic measurement with respect to the track state in the abscence of noise
- Jacobian of the radar measurements with respect to the track state
- Jacobian of the radar measurement with respect to the track measurement
- A.7 Other functions
- A.8 Conversions with a digital elevation model
- A.9 Jacobians of the conversion between ENU and track coordinate systems
- Jacobian of the location conversion with respect to the location
- Jacobian of the location conversion with respect to the DEM model parameters
- Jacobian of the location conversion with respect to track state and DEM model parameters
- Jacobian of ENU velocity with resepect to the DEM parameters
- Jacobian of ENU velocity with resepect to the track location
- Jacobian of ENU velocity with resepect to the track velocity
- Jacobian of the ENU velocity with respect to the entire track state and the DEM parameters
- Jacobian of entire ENU state with respect to the entire track state and the DEM parameters
- Bibliography