R. Pribic

R. Pribic
Thales Nederland BV, The Netherlands · Sensors Advanced Developments, Delft

PhD

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35
Publications
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413
Citations

Publications

Publications (35)
Conference Paper
A stochastic approach to resolution is explored that uses information distances computed from the geometry of data models characterized by the Fisher information in cases with spatial-temporal measurements for multiple parameters. Stochastic resolution includes probability of resolution at signal-to-noise ratio (SNR) and separation of targets. The...
Conference Paper
Stochastic description of resolution is explored that includes probability of resolution and signal-to-noise ratio (SNR). Taking SNR into account is especially relevant in compressive acquisition typical for compressive sensing (CS) due to the fact that fewer measurements are acquired. Our stochastic approach to resolution uses information distance...
Conference Paper
Sparse reconstruction techniques have recently been gaining traction as an alternative to traditional detection methods. In this paper, we develop fast methods for using sparse reconstruction techniques in a detection framework. We will show that these techniques may attain higher statistical power than the conventional matched filtering method. In...
Conference Paper
A bound for sparse reconstruction involving both the signal-to-noise ratio (SNR) and the estimation grid size is presented. The bound is illustrated for the case of a uniform linear array (ULA). By reducing the number of possible sparse vectors present in the feasible set of a constrained l 1 -norm minimization problem, ambiguities in the reconstru...
Conference Paper
Resolution from co-prime arrays and from a full ULA of the size equal to the virtual size of co-prime arrays is investigated. We take into account not only the resulting beam width but also the fact that fewer measurements are acquired by co-prime arrays. This fact is relevant in compressive acquisition typical for compressive sensing. Our stochast...
Conference Paper
Full-text available
Angular resolution can be improved by using co-prime arrays instead of uniform linear arrays (ULA) with the same number of elements. We investigate how the possible co-prime angle resolution is related to the angle resolution from a full ULA of the size equal to the virtual size of co-prime arrays. We take into account not only the resulting beam w...
Conference Paper
Compressive sensing (CS) in radar is presented at the system level with emphasis on the front end that keeps the functionality of data acquisition. In CS, the data acquisition is compressive as it delivers fewer measurements. We explore spatial compressive acquisition of radar measurements by the existing means available in a radar system: design o...
Article
Design of radar grid cells is based on the resolution of radar processing. In typical radar, the cell size is constant, i.e. the estimation grid is regular. However, the resolution is not constant, as it increases at closer ranges due to stronger radar echoes. Radar resolution is computed from the intrinsic geometrical structure of data models that...
Article
Full-text available
Radar obtains its parameters on a grid whose design supports resolution of underlying radar processing. Existing radar exploits a regular grid although the resolution changes with stronger echoes at shorter ranges. We compute the radar resolution from the intrinsic geometrical structure of data models that is characterized in terms of the Fisher in...
Patent
Full-text available
A method for estimating the position and the speed of a target with a radar is provided. The radar emits a waveform including a train of pulses, each pulse having an OFDM chip constructed from subcarriers, the subcarriers covering the whole bandwidth of the radar. Upon receipt of the echoed pulses, some of the subcarriers are used in a step of Dopp...
Conference Paper
Bayesian compressive sensing using Monte Carlo methods is able to handle non-linear, non-Gaussian signal models. The computational expense associated with Monte Carlo methods is, however, a concern especially in scenarios requiring real-time processing. In this work, a theoretical model is derived that provides insight on the relationship between p...
Conference Paper
Radar obtains its parameters on an estimation grid whose cell size is related to resolution of underlying radar processing. Existing radar exploits a regular grid (i.e. constant resolution) although the resolution changes with stronger echoes at shorter ranges.We compute radar resolution from the intrinsic geometrical structure of data models that...
Conference Paper
Full-text available
Sparse-signal processing (SSP) is interpreted in this paper as a sparse model-based refinement of typical steps in radar processing. Matched filtering remains vital within SSP but joined with radar detection promoting the sparsity. Realistic measurements are also supported in SSP by using Monte-Carlo (MC) methods. MC-based SSP promotes the sparsity...
Article
Traditional radar detection schemes are typically studied for single target scenarios and they can be non-optimal when there are multiple targets in the scene. In this paper, we develop a framework to discuss multi-target detection schemes with sparse reconstruction techniques that is based on the Neyman-Pearson criterion. We will describe an initi...
Conference Paper
Sparse signal reconstruction from compressive measurements assumes a grid of possible support points from which to estimate the signal support set. However, reconstruction of high measurement resolution waveforms is very sensitive to small grid offsets and assuming a fixed grid may result to information loss. On the other hand, identifying sparse e...
Article
Full-text available
The problem of reconstructing a signal from compressively sensed measurements is solved in this work from a Bayesian perspective. The proposed reconstruction solution differs from previous Bayesian methods in that it numerically evaluates the posterior of the sparse solution. This allows the method to utilize any kind of information on the signal w...
Article
Full-text available
The performance of conventional radar is foreseen to be improved by the implementation of compressive sensing (CS). CS is based on the assumptions of sparsity and incoherence. Here we connect the incoherence of the sensing matrix and the autocorrelation of a radar waveform, and use them as a measure for the design of an optimal waveform in CS based...
Conference Paper
Full-text available
Sparse signal recovery is often performed over an estimation grid whose choice affects the recovery performance. The grid mismatch effect is posed as a total least squares problem based on the errors in variables (EIV) model. An existing approach to model the mismatch namely the interpolation approach is interpreted as an EIV model. The grid mismat...
Conference Paper
Full-text available
Compressive sensing (CS) is a new tool that intends to estimate the original information by means of convex optimization, using just a few measurements. In radar this original information consists of the range - Doppler map of the observed scene. The method allows undersampling since the band-limitedness of the waveform is no longer the limiting cr...
Conference Paper
High range resolution (HRR) is an important feature for radar, aiming at target classification. The range resolution is inversely proportional to the bandwidth of the transmitted signal. Pulse burst waveforms can achieve HRR at low expenses when the carrier frequency increases from one pulse to the next, stepping and synthesizing the wide bandwidth...
Conference Paper
The use of multicarrier (MC) signals could support a new generation of radar that would provide simultaneously RF agility and Doppler processing. Easy to generate in digital signal processing (DSP), the well-known orthogonal frequency division multiplexing (OFDM), originally a communication waveform, is a first choice candidate. Its flexible struct...
Conference Paper
Frequency agility is an important feature when radar operates in jammed environments. With the development of the orthogonal frequency division multiplexing (OFDM) waveform in the communications, the opportunity for a new generation of digital agile radar rises. Old and expensive multi-channel analog agile front ends could be replaced by simpler an...
Conference Paper
Irregular pulse repetition time (PRT) implies irregularly sampled signals in pulse radar. Irregular PRT is intentional because it improves the radar anti-jamming performance. This radar specific case involves not only standard analysis from irregular samples but also demands additional research. The frequencies above the sampling frequency should b...
Article
Irregular Pulse Repetition Time (PRT) implies irregular sampling in pulse radar. It is intentional because it improves the radar anti-jamming performance. This radar specific case involves not only standard spectral analysis from irregular samples but also demands additional research. The frequencies above the sampling frequency should be sought an...
Conference Paper
Irregular PRT improves the radar ECCM performance, but implies irregularly sampled signals. Conventional Doppler processing can not suffice, because it is based on regular samples. Furthermore, the Nyquist sampling criterion cannot be met, because both time delays and Doppler frequencies are to be extracted from the radar samples. Applicability of...
Article
The isolated CP47-reaction center complex of spinach photosystem II has been studied with time resolved picosecond fluorescence spectroscopy between 77 K and 270 K. It was observed that these particles exhibit multi-exponential fluorescence decays of the excited state at all temperatures. The major observations are an energy transfer/trapping time...
Article
Gaining information on the secondary structure of a protein from its spectra is presented as a calibration problem. The secondary structures known from X-ray studies and the spectra of 21 proteins are represented by a linear model. Fourier transform infrared (FTIR) spectra from 1700 to 1600 cm-1, circular dichroism (CD) spectra from 178 to 260 nm,...
Article
A multiresponse nonlinear model being applied for global analysis of exponential decay data, is simulated. Exponential decays are present in several types of time resolved spectra. In an exponential sum model the nonlinear parameters are the decay rates, whereas their amplitudes as a function of wavelength are the conditionally linear parameters. A...
Article
A multivariate linear model (Gauss-Markoff model) with noise is used to analyze the estimation of protein secondary structure from spectra of 21 reference proteins whose structures are known from X-ray studies. Fourier transform infrared (FTIR) spectra from 1700 to 1500 cm-1 and circular dichroism (CD) spectra from 178 to 260 nm have been used. The...

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