Resolution analysis of GEO spaceborne-airborne bistatic SAR based on sliding spotlight mode

For a synthetic aperture radar（SAR） system mounted on a geostationary Earth orbit（GEO） satellite, the track can be curvilinear. Thus, a bistatic SAR system based up on geostationary transmitter and ＂receive-only＂ SAR system onboard airplanes, namely GEO spaceborne-airborne bistatic（GEO SA-Bi SAR）, is significantly different from the traditional bistatic SAR. This paper mainly studies the resolution characteristic of the sliding spotlight GEO SA-Bi SAR system. Firstly, the common azimuth coverage and coherent accumulated time are theoretically analyzed in detail. Then,based on the gradient method, the accurate two dimensional resolution of a GEO SA-Bi SAR system is analytically calculated. Finally, the simulation data show the correctness and effectiveness of the proposed resolution analysis method.

Imaging algorithm of multi-ship motion target based on compressed sensing

An imaging algorithm based on compressed sensing（CS） for the multi-ship motion target is presented. In order to reduce the quantity of data transmission in searching the ships on a large sea area, both range and azimuth of the moving ship targets are converted into sparse representation under certain signal basis. The signal reconstruction algorithm based on CS at a distant calculation station, and the Keystone and fractional Fourier transform（FRFT） algorithm are used to compensate range migration and obtain Doppler frequency. When the sea ships satisfy the sparsity, the algorithm can obtain higher resolution in both range and azimuth than the conventional imaging algorithm. Some simulations are performed to verify the reliability and stability.

Embedding any desired number of coexisting attractors in memristive system

A simple variable-boostable system is selected as the structure for hosting an arbitrarily defined memristor for chaos producing.The derived three-dimensional(3-D)memristive chaotic system shows its distinct property of offset,amplitude and frequency control.Owing its merits any desired number of coexisting attractors are embedded by means of attractor doubling and self-reproducing based on function-oriented offset boosting.In this circumstance two classes of control gates are found:one determines the number of coexisting attractors resorting to the independent offset controller while the other is the initial condition selecting any one of them.Circuit simulation gives a consistent output with theoretically predicted embedded attractors.

Data-driven Two-step Day-ahead Electricity Price Forecasting Considering Price Spikes

In the electricity market environment,electricity price forecasting plays an essential role in the decision-making process of a power generation company,especially in developing the optimal bidding strategy for maximizing revenues.Hence,it is necessary for a power generation company to develop an accurate electricity price forecasting algorithm.Given this background,this paper proposes a two-step day-ahead electricity price forecasting algorithm based on the weighted Knearest neighborhood(WKNN)method and the Gaussian process regression(GPR)approach.In the first step,several predictors,i.e.,operation indicators,are presented and the WKNN method is employed to detect the day-ahead price spike based on these indicators.In the second step,the outputs of the first step are regarded as a new predictor,and it is utilized together with the operation indicators to accurately forecast the electricity price based on the GPR approach.The proposed algorithm is verified by actual market data in Pennsylvania-New JerseyMaryland Interconnection(PJM),and comparisons between this algorithm and existing ones are also made to demonstrate the effectiveness of the proposed algorithm.Simulation results show that the proposed algorithm can attain accurate price forecasting results even with several price spikes in historical electricity price data.