Rustem B. Sinitsyn

Kernel estimates of the characteristic function for radar signal detection

The paper presents a new approach to synthesis of nonparametric algorithms, which can be used in different types of radars. Nonparametric algorithms of radar signal detection, using kernel estimates of characteristic function, were developed and tested for detecting different types of radar signals. The results were tested with the help of Monte-Carlo simulation as well as the physical radar model

Copula ambiguity function for wideband random radar signals

In this paper we suggest the improvement and generalization of the wideband ambiguity function for radar signals. Sounding waveforms and reflected radar signals have different probability density functions, and this fact is not taken into account in classical definition of an ordinary ambiguity function. The proposed generalization of the ambiguity function is based on the copula notion and does not depend on a probability density function. The generalized copula ambiguity function is useful for both analysis/synthesis of sounding waveforms (auto-ambiguity) and reflected signal detection/measurement (cross-ambiguity). Application of this approach gets rid of a dependence on the signal probability distribution, implementing actually non-parametric approach with CFAR.

Ultrawideband Signal Processing Algorithms for Radars and Sodars

In this paper we use statistical approach to synthesize algorithms for digital signal processing in UWB noise radar and sodar. Parametrical and non-parametrical algorithms are synthesized and analyzed. Experimental check is done on the basis of developed acoustic physical model which is used to build a noise sodar prototype. Developed algorithms can be used in noise radars for different applications. The use of the UWB noise signal provides a very high resolution both in speed and range

Generalized copula ambiguity function application for radar signal processing

This paper presents a new approach to the definition of the radar ambiguity function. Using the notion of the copula a nonparametric extension of the wideband ambiguity function for random radar signals is suggested. This notion can be used for nonparametric signal detection and also for the radar signal analysis.

Reliability of detection of radar signals from hailstones by using parametric and non-parametric algorithms

New algorithms for polarimetric radar signals processing were developed and applied for the detection of hail zones in clouds and precipitation. This paper presents and analyzes two algorithms: parametric algorithm and adaptive non-parametric algorithm. Reliability of detection of radar signals from hailstones is investigated by statistical simulation with application of experimental researches as initial data. The results demonstrate the limits of both algorithms as well as higher viability of non-parametric algorithm. Polarimetric algorithms are useful for the implementation in ground-based and airborne weather radars

Passive acoustic radar for aircraft trajectory tracking

In this paper the algorithm of signal detection for passive acoustic radar is proposed. This algorithm is based on processing of multiple input signals, which are received from several acoustic aerials with some number of microphones in each of them. For the signal processing the original algorithm of calculation of wide-band ambiguity function together with its projection on time axis is used. The suggested algorithm is proposed to use for measuring of aircraft noise with the aim of environmental protection.

Ambiguity function of passive acoustic radar

The sound from a flying aircraft is received and recorded. The passive acoustic radar ambiguity function is measured and processed. This gives the possibility of calculation of the aircraft coordinates and its velocity.

Copula based dependence measure for polarimetric weather radar

In this paper we suggest a new nonparametric description for parameters connecting signals in polarimetric weather radar. This extension gives us a possibility of obtaining reflected signal description parameters not depending from the polarimetric signal two-variable probability density function. The approach is based on comparatively new statistical notion - copula.

Invariant polarimetric parameters for signal processing in weather radar

In this paper we introduce and check a new description of polarimetric parameters that are asymptotically invariant to the group of all monotonous transformations of input signals. In particular, this can give a possibility to estimate pure correlation between polarimetric signals independently on statistical characteristics of initial data. This copula-based approach is applied to signal processing in polarimetric meteorological radar.

Retrieving aircraft motion parameters, using acoustic passive radar

This paper presents the method and a special approach to signal processing in acoustic passive radar for retrieving aircraft motion parameters. The algorithm of aircraft position determination based on its acoustic noise measurement is developed. This algorithm makes processing of multiple input signals, which are received from several acoustic aerials with definite number of microphones in each of them. The original algorithm of calculation of wide-band ambiguity function together with its projection on time axis is used. Also, the method of obtaining aircraft velocity vector is proposed.