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This paper aims to present, design and implement a novel half-mode substrate integrated waveguide (HMSIW)-based narrow bandpass filter, which offers advantages like low insertion loss, compact size and high selectivity. Proposed filter will be used in the K-band automotive radar application.

The filtering response in the proposed design is achieved by inserting inductive posts in the HMSIW cavity. Ansoft high frequency structure Simulator (HFSS) is used for the simulation of the proposed structure, which is a three-dimensional full-wave solver using the finite element method (FEM). The proposed filter is fabricated on the dielectric material RT duroid 5,880 with the dielectric constant ɛ_r = 2.2, dissipation factor t and = 4 × 10^–4 and height h = 0.508 mm.

Frequency tuning is also carried out by changing the lateral distance between two inductive posts. Moreover, a comparison of the proposed structure with the previously published work is presented. Proposed method provides the unique advantages such as low insertion loss, high selectivity and compact in size.

Indigenous method has been used for the development of the filter. Proposed filter will be used in transmitter subsystem of the K-band radar system operating at the center frequency of 11.2 GHz. Measurement results are well-matched with the simulated one. Obtained measured result shows return loss of 20.39 dB and insertion loss of 1.59 dB with 3 dB fractional bandwidth (FBW) of 2.58% at the center frequency of 11.2 GHz.

Synthetic aperture radar (SAR) imaging is the most computational intensive algorithm and this makes its implementation challenging for real-time application. This paper aims to present the chirp-scaling algorithm (CSA) for real-time SAR applications, using advanced field programmable gate array (FPGA) processor.

A chirp signal is generated and compressed using range Doppler algorithm in MATAB for validation. Fast Fourier transform (FFT) and multiplication operations with complex data types are the major units requiring heavy computation. Therefore, hardware acceleration is proposed and implemented on NEON-FPGA processor using NE10 and CEPHES library.

The heuristic analysis of the algorithm using timing analysis and resource usage is presented. It has been observed that FFT execution time is reduced by 61% by boosting the performance of the algorithm and speed of multiplication operation has been doubled because of the optimization.

Very few literatures have presented the FPGA-based SAR imaging implementation, where analysis of windowing technique was a major interest. This is a unique approach to implement the SAR CSA using a hybrid approach of hardware–software integration on Zynq FPGA. The timing analysis propagates that it is suitable to use this model for real-time SAR applications.

The purpose of this paper is to design and develop half-mode substrate-integrated waveguide (HMSIW)- and quarter-mode substrate-integrated waveguide (QMSIW)-based antennas for wireless communication application. The developed antennas offer advantages in terms of compactness, high gain and better isolation between the ports.

Initially, the tri-band substrate-integrated waveguide-based antenna is designed using a slot on the ground plane. Then, the same structure has been bisected into two parts for the development of the HMSIW structure. Again the concept of the slot is used for the realization of a dual-band antenna. QMSIW-based structure is designed with further dividing HMSIW structure into two parts. Simulation has been carried out with the use of a high-frequency structure simulator (HFSS) software, which used a finite element-based solver for the full-wave analysis.

The proposed HMSIW-based dual-band antenna resonates at two different frequencies, namely, 5.81 GHz with 4.5 dBi gain and at 6.19 GHz with 6.8 dBi gain. Isolation between two ports is 20 dB. The overall dimensions of the proposed model are 0.39 λ × 0.39 λ. Similarly, QMSIW-based antenna is resonated at 5.66 GHz of the frequency with the 3 dBi gain. Frequency tuning is also carried out with the change in the slot dimension to use the proposed antenna in various C (4–8 GHz) band applications.

The proposed antennas can use C band wireless frequency application. The proposed structure provides better performance in terms of isolation between the ports, small size, high front-to-back ratio and higher gain. It is fabricated for the proof of concept with the RT Duroid 5880 substrate material having a 2.2 permittivity. Measured results show a similar kind of performance as a simulated one.

The digital down converter (DDC) is a principal component in modern communication systems. The DDC process traditionally entails quadrature down conversion, bandwidth reducing filters and commensurate sample rate reduction. To avoid group delay, distortion linear phase FIR filters are used in the DDC. The filter performance specifications related to deep stopband attenuation, small in-band ripple and narrow transition bandwidth lead to filters with a large number of coefficients. To reduce the computational workload of the filtering process, filtering is often performed as a two-stage process, the first stage being a down sampling Hoegenauer (or cascade-integrated comb) filter and a reduced sample rate FIR filter. An alternative option is an M-Path polyphase partition of a band cantered FIR filter. Even though IIR filters offer reduced workload to implement a specific filtering task, the authors avoid using them because of their poor group delay characteristics. This paper aims to propose the design of M-path, approximately linear phase IIR filters as an alternative option to the M-path FIR filter.

Two filter designs are presented in the paper. The first approach uses linear phase IIR low pass structure to reduce the filter’s coefficient. Whereas the second approach uses multipath polyphase structure to design approximately linear phase IIR filter in DDC.

The authors have compared the performance and workload of the proposed polyphase structured IIR filters with state-of-the-art filter design used in DDC. The proposed design is seen to satisfy tight design specification with a significant reduction in arithmetic operations and required power consumption.

The proposed design is an alternate solution to the M-path polyphase FIR filter offering very less number of coefficients in the filter design. Proposed DDC using polyphase structured IIR filter satisfies the requirement of linear phase with the least number of computation cost in comparison with other DDC structure.

In clinical analysis, medical image segmentation is an important step to study the anatomical structure. This helps to diagnose and classify abnormality in the image. The wide variations in the image modality and limitations in the acquisition process of instruments make this segmentation challenging. This paper aims to propose a semi-automatic model to tackle these challenges and to segment medical images.

The authors propose Legendre polynomial-based active contour to segment region of interest (ROI) from the noisy, low-resolution and inhomogeneous medical images using the soft computing and multi-resolution framework. In the first phase, initial segmentation (i.e. prior clustering) is obtained from low-resolution medical images using fuzzy C-mean (FCM) clustering and noise is suppressed using wavelet energy-based multi-resolution approach. In the second phase, resultant segmentation is obtained using the Legendre polynomial-based level set approach.

The proposed model is tested on different medical images such as x-ray images for brain tumor identification, magnetic resonance imaging (MRI), spine images, blood cells and blood vessels. The rigorous analysis of the model is carried out by calculating the improvement against noise, required processing time and accuracy of the segmentation. The comparative analysis concludes that the proposed model withstands the noise and succeeds to segment any type of medical modality achieving an average accuracy of 99.57%.

The proposed design is an improvement to the Legendre level set (L2S) model. The integration of FCM and wavelet transform in L2S makes model insensitive to noise and intensity inhomogeneity and hence it succeeds to segment ROI from a wide variety of medical images even for the images where L2S failed to segment them.