Since trellis-coded modulation (TCM) was introduced, it was quickly adopted in modem standards. Unlike blind reconstruction for normal channel coding, blind reconstruction for TCM codes not only requires identifying the correct generator matrix, but also the correct type of constellation mapping. So far this has seldom been reported. This study proposes a method which recognises the generator matrix and the mapping mode of TCM codes. Based on its construction and properties, the generator matrix can be correctly identified by considering the characteristics of the actual communication system. That is, its Euclidean distance and Hamming distance are considered to discover the mapping mode. Simulations prove that the methodology can realise the blind identification of TCM codes efficiently.

In this paper, the modified prominent point processing (MPPP) approach for the phase compensation in inverse synthetic aperture radar (ISAR) imaging is proposed. It applies the minimum entropy method (MEM) to find the prominent point cell used for the phase calibration. After minusing the measured phase value of prominent point range cell from all the range bins belonged to the same echo, a well-focused ISAR image can be obtained by combining all the range bins. Compared to the PPP algorithm, the MPPP method can find the better prominent point unit utilized for the phase correction, which will lead to a more focused ISAR image after the phase compensation. The simulation result proves that the proposed approach can enhance the clarity and focusing of the ISAR image.

Constrained interleaved coded modulation technique known to map coded bits of outer block codes onto a higher-order constellation is extended with suitable adjustments for outer convolutional codes. A novel puncturing technique based on the mapping is proposed to generate powerful punctured coded schemes. It is demonstrated that the proposed mapping and puncturing techniques are significantly better than their traditional counterparts.