Small Target Detection Within Sea Clutter Based on Fractal Analysis

AbstractSea clutter refers to the signals returned from the wavy and turbulent rough sea surface. The radar returns from small targets, like submarine periscope or small boats, will be obscured by the sea clutter which makes the straightforward detection of targets, with small radar cross section, a difficult task. The conventional target detection schemes in the presence of sea clutter are mainly based on Hurst exponent, estimated utilizing the fractal characteristics of the received radar data. In the present study, a more robust signature measure is proposed based on fractal analysis of received radar data. The proposed target detection method is applied on actual sea clutter radar data and the performance is compared with the conventional Hurst parameter based method. The simulation results illustrate that the proposed method achieves better detection performance and is robust under varying sea conditions

Optimized-Fuzzy-Logic-Based Bit Loading Algorithms

Next generation wireless communication systems promise the subscribers with Giga-bit-data-rate experience at low Bit Error Rate (BER) under adverse channel conditions. In order to maximize the overall system throughput of Orthogonal Frequency Division Multiplexing (OFDM), adaptive modulation is one of the key solutions. In adaptive modulated OFDM, the subcarriers are allocated with data bits and energy in accordance with the Signal to Interference Ratio (SIR) of the multipath channel, which is referred to as adaptive bit loading and adaptive power allocation respectively. The number of iterations required allocating the target bits and energy to a sub channel is optimized. The key choice of the paper is to allocate the bits with minimum number of iterations after clustering the sub channels using fuzzy logic. The proposed method exhibits a faster convergence in obtaining the optimal solution. </jats:p