Al-Abbass Al-Habashneh

Reliability analysis of Wireless Sensor Networks for forest fire detection

The transport reliability is a very important feature in Wireless Sensor Networks (WSN), particularly in some critical applications such as forest fire detection. In this paper, we propose reliability enhancement mechanisms in order to improve the reliability of three MAC protocols we proposed in [1] for forest fire detection. We evaluate the reliability performance analytically and by simulation. Results show that a significant enhancement in the transport reliability is achieved due to the proposed mechanisms. Furthermore, we show that the reliability enhancement is achieved with a very slight increase in the energy consumption and packet delay.

An Adaptive Method of Wave Spectrum Estimation Using X-Band Nautical Radar

In this paper, the dependency of wave spectrum estimation on the analysis window orientation for X-band marine radar data is investigated. The investigation is made for the case where both wind wave and swell components are present. Our results show that more accurate and reliable wave spectrum estimates are obtained when one analysis window for each component (wind waves or swell) is used and is oriented in the up-wave direction of that component. The final wave spectrum estimation is found by averaging the output of those analysis windows. Since the direction of wind waves and swell is not known a priori, a new method is proposed to recursively determine the number and orientation of analysis windows. This method is referred to as the Adaptive Recursive Positioning Method (ARPM). For validation, ocean wave spectra are estimated from X-band marine radar field data using the ARPM and the standard method, using uniformly distributed analysis windows. The results from both methods are compared to ground truth wave spectra acquired using waverider buoy data. Results have shown that the ARPM produces a 10% improvement in the agreement (represented by the correlation coefficient) between the ground truth wave spectrum and the marine radar estimated wave spectrum. This improvement is reflected in a 15% to 30% accuracy enhancement in the wave period estimation and 6 ∘ in peak wave direction. The ARPM not only increases the accuracy of wave period and direction estimation, but it also increases the method’s reliability by producing a lower error standard deviation. Although these improvements are at the price of extra computational time, it has been found that this overhead is acceptable since it is far from the upper bound that requires offline analysis.

Ocean wave spectrum estimation from marine radar data using the polar fourier transform

The Polar Fourier Transform (PFT) can be used to estimate the ocean wave number spectrum from marine radar data. The main advantage of the PFT over the Cartesian Fourier Transform (CFT) is its direct applicability to the native radar data without the need for the intermediate stage of scan conversion. However, by definition, the PFT operates on positive, and not negative, wavenumbers. This leads to a problem in estimating the ocean wave spectrum which may contain negative wavenumbers. Therefore, a process of wavenumber mapping is proposed in order to circumvent this problem. In this technique, which is implemented before applying the PFT, the wave number content of the radar signal is compressed by a factor of 1/2 and shifted by π/2. This mapping migrates all wave numbers to fit into the range of 0 to π so that the PFT is required to deal with only positive wavenumbers.

A hybrid method for surface current estimation using X-band nautical radar

In this paper, a new method is proposed to estimate surface current using X-band nautical radar. This method is referred to as the Hybrid Least Squares (HLS) method. The HLS combines the existing Iterative Least Squares (ILS) and Normalized Scalar Product (NSP) methods. The HLS is designed to inherit the short ILS computational time and the high NSP reliability. For validation, the proposed method was applied on a number of simulated X-band nautical radar image sets. Results have shown that the HLS produces accurate estimates while maintaining very short computational time.

Performance of the Polar Fourier transform for ocean wave spectrum estimation from marine radar

Scan conversion, as a re-sampling process, is expected to add non-wave components to the wave spectrum. Resampling processes involve applying a low-pass filter to retrieve the original image followed by sampling on the new Cartesian grid. Scan conversion is necessary for ocean wave spectrum estimation using the Cartesian Fourier Transform (CFT). The Polar Fourier Transform (PFT) was originally proposed to avoid this intermediate stage and apply the transformation directly on the radar native form. In this paper, which incorporates field data, the PFT performance in estimating the wave spectrum is tested and compared to results from the CFT. Results show that the PFT outperforms the CFT at lower threshold values. This may imply that part of the noise added to the spectrum is due to the scan conversion process.