A novel approach for the parameter estimation of the polynomial phase signals (PPS) based on the short‐time Fourier transform (STFT) is proposed. Estimator accuracy is significantly higher compared to the high‐order ambiguity function (HAF), product HAF, and similar the non‐linear transforms based strategies. The proposed approach is more efficient than the maximum likelihood (ML) estimator for the high‐order PPS. One‐dimensional search is performed over a set of window widths in the STFT, whereas in the case of ML estimators, it has been done over the space of phase parameters. The proposed estimator is implemented in several steps: the instantaneous frequency (IF) estimation using the STFT for various window widths; a polynomial regression from the IF estimate producing a coarse signal coefficients estimate; refinement procedure, producing fine coefficients estimates; determination of the optimal window width in the STFT. The proposed technique is extended for the non‐parametric estimation with a 2D search over a set of polynomial orders and window widths. Good estimation results are achieved up to the SNR threshold of about SNR=0 dB for the parametric case and SNR=2 dB for the non‐parametric case.

Effective quasi maximum likelihood - random samples consensus algorithm is proposed for the instantaneous frequency (IF) estimation of overlapping signals in the time-frequency (TF) plane. The proposed algorithm is tested on signal with five overlapping components. The IF estimation accuracy is excellent with signal-to-noise ratio threshold below 0 dB.

There is a significant recent advance in filtering of the salt-and-pepper noise for digital images. However, almost all recent schemes for filtering of this type of noise are not taking into an account the shape of objects (in particular edges) in images. We have applied the block-matching and 3D filtering (BM3D) scheme in order to refine the output of the decision-based/adaptive median techniques. Obtained results are excellent, surpassing current state-of-the-art for about 2 dB for both grayscale and color images.

Automatic modulation recognition plays a vital role in electronic warfare. Modern electronic intelligence and electronic support measures systems are able to automatically distinguish the modulation type of an intercepted radar signal by means of real-time intra-pulse analysis. This extra information can facilitate deinterleaving process as well as be utilized in early warning systems or give better insight into the performance of hostile radars. Existing modulation recognition algorithms usually extract signal features from one of the rudimentary waveform characteristics, namely instantaneous frequency (IF). Currently, there are a small number of studies concerning IF estimation methods, specifically for radar signals, whereas estimator accuracy may adversely affect the performance of the whole classification process. In this paper, five popular methods of evaluating the IF–law of frequency modulated radar signals are compared. The considered algorithms incorporate the two most prevalent estimation techniques, i.e., phase finite differences and time-frequency representations. The novel approach based on the generalized quasi-maximum likelihood (QML) method is also proposed. The results of simulation experiments show that the proposed QML estimator is significantly more accurate than the other considered techniques. Furthermore, for the first time in the publicly available literature, multipath influence on IF estimates has been investigated.

This paper relates to three strategies of SAR image lossy compression by wavelet based coders as JPEG2000 and SPIHT. We take into account two aspects: 1) the inherent presence of speckle and its features; 2) filtering effect of lossy compression if applied to noisy images. The first strategy is visually lossless compression. According to the second strategy, a fixed compression ratio (CR) has to be provided. The third strategy is to perform compression in the neighborhood of optimal operation point (OOP). For all strategies, compression with and without logarithmic type homomorphic transform (HT) is considered. It is shown that the use of HT produces several benefits.