Lothar Kurz

An architecture for an embedded antenna-array digital GNSS receiver using subspace-based methods for spatial filtering

This paper presents an architecture for an embedded multi-antenna digital GNSS receiver. A two-stage adaptive beamformer for interference suppression and Line-of-Sight (LoS) signal amplification is presented and analyzed w.r.t. to an efficient implementation on embedded receivers. Jammer signals are mitigated at pre-correlation stage whereas the LoS signals are amplified at post-correlation stage. The method is based on a subspace-based approach where filter coefficients are derived from the eigenvalues and -vectors of the covariance matrix. In the first stage, the covariance matrix is determined immediately from the digital antenna signals for interference mitigation and in the second stage, the matrix is computed based on the correlator outputs of each satellite in LoS. Dedicated buildingblocks for covariance matrix estimation and filtering are required for interference mitigation since this operation is computed on sampling rate. A fixed-point VHDL implementation and related costs in terms of logic-cell requirements on an FPGA are provided for both blocks. Eigendecomposition is computed on an embedded processor. The implementation of two decomposition algorithms (one for interference mitigation and the other one for LoS-signal amplification) are presented. Optimizations and costs in terms of processing-cycles on an embedded processor are provided.

JamCam: A camera-integrated GNSS receiver for spatial detection of radio frequency interference sources

This paper presents a Global Navigation Satellite System (GNSS) array-antenna receiver which is capable of generating source-maps of Radio Frequency Interference (RFI) to be superimposed to real-world pictures obtained from a camera. The principle is similar to the acoustic camera which is used for localization of acoustic noise sources in an image or a video sequence. Source-map generation is generally based on Direction-of-Arrival (DoA)-estimation techniques. In case of the GNSS-receiver, the Multiple Signal Identification and Classification (MUSIC) technique has been adopted for spectral DoA-estimation. Amplitudes in the spectrum indicate the DoA of RFI-sources depending on azimuth and elevation angles in the hemisphere above the array-antenna. These coordinates are transferred into cartesian image coordinates and an overlay image is generated with colors reflecting the shape of the spectrum. Afterwards, this image is superimposed to a grayscale picture obtained from the camera and RFI-sources can be visualized in the image. In this context, the paper addresses issues for online calibration of the array-antenna and static calibration of the camera. An Field Programmable Gate Array (FPGA)-based demonstrator is presented and first results from testing the receiver in real-time in an anechoic chamber are discussed.

Efficient computation of the position, velocity and time estimation algorithm on a GNSS processor using interpolation

Computational load of a highly complex function can be reduced by generating precise samples and interpolating for the data points between the samples. In this paper, application of the polynomial interpolation to two performance critical sub-functions of the position, velocity and time estimation algorithm is studied, namely (1) computation of satellite position and clock correction for each satellite in line-of-sight and (2) corrections of atmospheric delays in the pseudo-ranges.