| State estimation of linear dynamic system with unknown input and uncertain observation using dynamic programming D Janczak, Y Grishin Control and Cybernetics 35 (4), 2006 | 52 | 2006 |
| State estimation of linear dynamic system with unknown input and uncertain observation using dynamic programming D Janczak, Y Grishin Control and Cybernetics 35 (4), 851-862, 2006 | 52 | 2006 |
| Radar signal recognition based on time-frequency representations and multidimensional probability density function estimator K Konopko, YP Grishin, D Jańczak 2015 Signal Processing Symposium (SPSympo), 1-6, 2015 | 28 | 2015 |
| Detection of LFM radar signals and chirp rate estimation based on time-frequency rate distribution E Swiercz, D Janczak, K Konopko Sensors 21 (16), 5415, 2021 | 14 | 2021 |
| Accuracy analysis of the indoor location system based on Bluetooth low-energy RSSI measurements D Janczak, W Walendziuk, M Sadowski, A Zankiewicz, K Konopko, ... Energies 15 (23), 8832, 2022 | 12 | 2022 |
| Estimation and classification of nlfm signals based on the time–chirp representation E Swiercz, D Janczak, K Konopko Sensors 22 (21), 8104, 2022 | 12 | 2022 |
| Data fusion for ballistic targets tracking using least squares D Janczak, M Sankowski AEU-International Journal of Electronics and Communications 66 (6), 512-519, 2012 | 12 | 2012 |
| An adaptive algorithm of state estimation in the presence of multiplicative interferences D Janczak Przegląd Elektrotechniczny 86, 30-31, 2010 | 11 | 2010 |
| Measurement fusion using maximum‐likelihood estimation of ballistic trajectories D Janczak, M Sankowski, Y Grishin IET Radar, Sonar & Navigation 10 (5), 834-843, 2016 | 8 | 2016 |
| A detection-estimation method for systems with random jumps with application to target tracking and fault diagnosis YP Grishin, D Janczak Nonlinear Dynamics, INTEH 1, 343-366, 2010 | 8 | 2010 |
| Using the Hough transform as a track initiator in A TBD system Y Grishin, E Swiercz, D Janczak Proc. IRS 4, 291-296, 2004 | 7 | 2004 |
| Time-chirp distribution for detection and estimation of LPI radar signals E Swiercz, K Konopko, D Janczak 2020 21st International Radar Symposium (IRS), 362-367, 2020 | 6 | 2020 |
| Computer-aided methods of the LPI radar signal detection and classification Y Grishin, D Janczak Photonics Applications in Astronomy, Communications, Industry, and High …, 2007 | 6 | 2007 |
| A new data processing algorithm for enhancing the measurement accuracy of monovalent alkaline metals microconcentration W Holiczer, Y Grishin, D Janczak, E Olech Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (IEEE …, 2004 | 5 | 2004 |
| Classification method based on multidimensional probability density function estimation dedicated to embedded systems K Konopko, D Janczak IFAC-PapersOnLine 51 (6), 318-323, 2018 | 4 | 2018 |
| An adaptive target tracking algorithm for fluctuating signals D Janczak, YP Grishin, A Nikolajew Photonics Applications in Astronomy, Communications, Industry, and High …, 2009 | 4 | 2009 |
| The GLR failure detection algorithm for a class of nonlinear dynamic models with application to radar tracking problems D Janczak, YP Grishin 2008 International Radar Symposium, 1-4, 2008 | 4 | 2008 |
| Identification of parameters of high order polynomial phase signals E Swiercz, D Janczak, K Konopko 2021 21st International Radar Symposium (IRS), 1-10, 2021 | 3 | 2021 |
| Nonlinear signal processing with minimization of spectral distortion for embedded systems K Konopko, D Janczak IFAC-PapersOnLine 51 (6), 450-455, 2018 | 3 | 2018 |
| Estimation method for measurements with heavy-tailed noise variance D Janczak Przegld Elektrotechniczny 1 (12), 24-27, 2017 | 3 | 2017 |
