Abstract-A microstrip line fed dual band-reject ultra wideband antenna with sharp band edge frequency of 3.1-10.6 GHz is presented. The antenna consists of a rectangular patch on the front side and a partial ground plane at the rear. A step is cut on the bottom edge of the patch for impedance matching. A split ring slot etched on the radiating patch rejects WiMAX (3.3-3.8 GHz) band, and a pair of inverted S-shaped slot in the partial ground plane rejects WLAN (5-6 GHz) band. In order to eliminate the radiation outside the FCC specified 3.1-10.6 GHz band, a rectangular slot is etched on the ground plane below the feed line. The antenna exhibits UWB band width of 109% except for the notch band. The radiation characteristics are consistent throughout the band. The performance of the antenna is analyzed both in the frequency domain and time domain to assess its suitability for ultra wideband communication. Pulse distortion of the antenna is investigated for both Rayleigh and Gaussian source pulse excitation.
This paper analyses the velocity estimation of a target, from the Doppler filter using 1) Kalman filter 2) Adaptive Kalman filter 3) Kalman filter with state vector fusion 4) Adaptive Kalman filter with state vector fusion 5) State vector fused adaptive Kalman filter. Simulation through MATLAB gave good response for 4 th and 5 th algorithms under low signal to noise ratio. 2 nd and 3 rd algorithms gave better results in intensive maneuvers. But 1 st algorithm even though it is low cost and faster, fails due to the delay in response.
KeywordsAdaptive Doppler Kalman filter, state vector fusion, intensive maneuver.
Estimating the position of a moving target in the polar frame of reference has been a major problem in the conventional tracking systems. The commonly used sensor equipment provides the position of target in polar coordinates i.e. in range and azimuth (or bearing) angle with respect to the sensor location. The use of simple Kalman filter increases the error in this case. For more accurate tracking, the Converted Measurement Kalman filter (CMKF) is used which can account for the inaccuracies in tracking using polar coordinates. Simulations were performed tracking the target with CMKF. It does not proffer well in missed detection and false alarm scenarios. So the tracking was improved by associating Global nearest Neighbour algorithm (GNN) algorithm with the CMKF. Later the simulations depict the inconsistency of GNN based CMKF in a dense missed detection and false alarm scenarios. So an improved algorithm in track estimation is used to solve the dense missed detections or continuous false alarm problem. Thus, through simulation, it was realized that GNN based improved CMKF is able to give a better tracking. Finally Wiener filtering is used to smoothen the tracking.
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