An automatic modulation classification algorithm for application in communications via multipath fading channels, without a priori information on channel characteristics, based on normalized sixth-order cumulants is described. In comparison with existing approaches, proposed algorithm can achieve much better classification accuracy in distinguishing BPSK from complex-valued modulation techniques. Theoretical analysis is verified via extensive simulations, under real-world channel propagation conditions.

An algorithm is described for estimation of multipath fading channels without a priori information on channel characteristics, for application in automatic modulation classification based on normalised sixth-order cumulants. Compared with existing approaches, the proposed algorithm can achieve much better classification accuracy in distinguishing complex-valued modulation techniques. Theoretical analysis is verified via extensive Monte-Carlo simulations.

In this paper an algorithm for automatic classification of unknown signal modulation formats, based on sixth-order cumulant features of received data samples, is analyzed. This algorithm is characterized with extremely low computational complexity and can be completely realized with modest digital resources. Also, it is capable to maintain significant classification performance, in the meaning of achieved probability of correct modulation format recognition, under the impact of various degradation sources: additive white noise, multipath propagation channels, or interference. These properties make the algorithm be perspective for practical implementation and potentially a good solution for wide set of military and commercial communication systems. Also, results of theoretical analysis of different properties of algorithm are presented, along with new channel estimation algorithm, proposed in literature for adoption within the system with automatic modulation classification. Some particular methods for improvement of algorithm's performance under specific propagation conditions are presented and discussed. Its performance has been compared with the best known classification algorithm, having similar implementation properties and capability to solve real-world issues, and verified through numerous Monte-Carlo simulations.

The monitoring of the sea surface, whether it is the state of the sea or the position of targets (ships), is an up-to-date research topic. In order to determine localization parameters of ships, we propose a high-resolution algorithm for primary signal processing in high-frequency surface wave radar (HFSWR) which operates at two frequencies. The proposed algorithm is based on a high-resolution estimate of the range–Doppler (RD-HR) map formed at every antenna in the receive antenna array, which is an essential task, because the performance of the entire radar system depends on its estimation. We also propose a new focusing method allowing us to have only one RD-HR map in the detection process, which collects the information from both these carrier frequencies. The goal of the bi-frequency mode of operation is to improve the detectability of targets, because their signals are affected by different Bragg-line interference patterns at different frequencies, as seen on the RD-HR maps during the primary signal processing. Also, the effect of the sea (sea clutter) manifests itself in different ways at different frequencies. Some targets are masked (undetectable) at one frequency, but they become visible at another frequency. By exploiting this, we increase the probability of detection. The bi-frequency architecture (system model) for the localization of sea targets and the novel signal model are presented in this paper. The advantage of bi-frequency mode served as a motivation for testing the detectability of small boats, which is otherwise a very challenging task, primarily because such targets have a small radar reflective surface, they move quickly, and often change their direction. Based on experimentally obtained results, it can be observed that the probability of detection of small boats can also be significantly improved by using a bi-frequency architecture.

In this letter, a new direct sequence spread spectrum scheme for protection of an unmanned aerial vehicle (UAV) binary pulse-position modulated (PPM)control signal is proposed. The UAV PPM control signal consists of data frames. Each of them contains a synchronizing pulse followed by a number of shorter pulses equal to the number of channels N. At the beginning of any pulse is the pause long 0.3 ms. The proposed scheme uses (N + 1) pseudonoise (PN) codes: one of them (PN₀) is assigned to the synchronizing pulse while the each of the remaining N codes (PN₁, PN₂, ... PN_N) corresponds to the appropriate channel. The same PN code is transmitted during the pause and the pulse which follows the pause. At the receiving side, the set of (N + 1) passive correlators is used to detect respective PN codes. Proposed scheme requires neither PN code tracking process nor data demodulation, so is resistant to timing jitter. Performance measures of the proposed scheme are calculated.