Krzysztof Kulpa

Bio: Krzysztof Kulpa is an academic researcher from Warsaw University of Technology. The author has contributed to research in topics: Radar & Passive radar. The author has an hindex of 26, co-authored 254 publications receiving 3084 citations.

Two Methods for Target Localization in Multistatic Passive Radar

Abstract: This paper compares two algorithms for three-dimensional target localization from passive radar measurements. The algorithms use bistatic range measurements from multiple transmitter-receiver pairs to calculate the target position. The algorithms derived are based on the methods known for time-difference-of-arrival (TDOA) systems, namely spherical interpolation (SI) and spherical intersection (SX). Both algorithms rely on closed-form equations. A theoretical accuracy analysis of the algorithms is provided. This analysis is verified with Monte-Carlo simulations and a real-life example is presented.

Masking effect and its removal in PCL radar

Abstract: Nowadays, passive coherent location (PCL) radar technology has become a subject of intensive investigations owing to its unique features, such as the absence of range and velocity ambiguity, low probability of interception (LPI), small size and low price. A study of PCL radar performance for the case when a distant, weak target echo is shadowed by strong echoes is presented. The presented method increases PCL radar performance in the distant zone by adaptive removal of strong echoes from the received signal.

Coherent MapDrift Technique

Abstract: A new parametric autofocus technique with a high accuracy of flight-parameter estimation dedicated to strip-mode synthetic aperture radar (SAR) systems is presented. Most of the known autofocus techniques require high-reflectivity targets (man-made targets) to obtain a properly focused SAR image. The technique proposed in this paper allows flight parameters to be estimated effectively, even for a low-contrast scene (e.g., forests, fields, small paths, etc.). The autofocus technique is based on well-known MapDrift (MD) principles. The presented technique is a coherent one, which allows flight parameters to be estimated more precisely than in the other well-known parametric technique referred to as classical MD. The presented technique allows flight parameters to be estimated with accuracy that is independent of the initial velocity error. It can be used for real-time processing for both Earth imaging and moving-target indication.

The CLEAN type algorithms for radar signal processing

Abstract: A new class of signal processing algorithm based on CLEAN methods primary introduced in radio-astronomy is presented in the paper The classical radar signal processing is based on match filtering concept, which is optimal in mean square sense in case, when single target echo is detected against white or colour Gaussian noise Such approach was effective when pulse radar have been widely used The introduction of pulse-compression technique changes significantly the signal model, but still the match filter have been widely The introduction of continuous wave radars, and especially noise and passive radars changed dramatically the situation In such radars all echoes are superimposed and interfere with each other and the simple model no longer fits to that case The straightforward solution - use of inverse problem mathematical solutions such as solving the set of nonlinear equations to find all echoes in received signal - is usually computationally ineffective and often numerically not stable, so suboptimal methods are being developed to improve detections of weak signals in CW radars One of possible solution is to use concept of CLEAN technique an remove all strong echoes from received signal When only weak signals and white noise remains in is possible to use matched filter concept without significant loses of radar sensitivity In the paper several techniques for radar signal processing utilizing CLEAN concept are shown

PaRaDe - PAssive RAdar DEmonstrator family development at Warsaw University of Technology

Abstract: The paper presents a family of passive coherent location (PCL) radar demonstrators, called PaRaDe (passive radar demonstrator), which were developed at Warsaw University of Technology. The systems exploit commercial FM radio transmitters as illuminators of opportunity in order to detect and track airborne targets. In the paper, the details of demonstrator systems are described and the results obtained in tests are presented.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

A Local Contrast Method for Small Infrared Target Detection

Abstract: Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Consequently, an effective small target detection algorithm inspired by the contrast mechanism of human vision system and derived kernel model is presented in this paper. At the first stage, the local contrast map of the input image is obtained using the proposed local contrast measure which measures the dissimilarity between the current location and its neighborhoods. In this way, target signal enhancement and background clutter suppression are achieved simultaneously. At the second stage, an adaptive threshold is adopted to segment the target. The experiments on two sequences have validated the detection capability of the proposed target detection method. Experimental evaluation results show that our method is simple and effective with respect to detection accuracy. In particular, the proposed method can improve the SNR of the image significantly.

Spotlight Synthetic Aperture Radar Signal Processing Algorithms

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