This is a book review of 'The Micro-Doppler Effect in Radar' by V. C. Chen. Artech House, 16 Sussex Street, London, SW1V 4RW, UK. 2011. 290pp + diskette. Illustrated. £90. ISBN 978-1-60807-057-2.

'The Micro-Doppler Effect in Radar' by V.C. Chen

The accurate classification of activity patterns based on radar signatures is still an open problem and is a key to detect anomalous behavior for security and health applications. This paper presents a novel iterative convolutional neural network strategy with an autocorrelation pre-processing instead of the traditional micro-Doppler image pre-processing to classify activities or subjects accurately. The proposed strategy uses an iterative deep learning framework for the automatic definition and extraction of features. This is followed by a traditional supervised learning classifier to label different activities. Using three human subjects and their real motion captured data, 12 000 radar signatures were simulated by varying additive white Gaussian noise. In addition, 6720 experimental radar signatures were captured with a frequency-modulated continuous radar at 5.8 GHz with 400 MHz of instantaneous bandwidth from seven activities using one subject and 4800 signatures from five subjects while walking. The simulated and experimental data were both used to validate our proposed method, with signal–noise ratio varying from −20 to 20 dB and with 88.74% average accuracy at −10 dB and 100% peak accuracy at 15 dB. The proposed iterative convolutional neural networks followed with random forests not only outperform the feature-based methods using micro-Doppler images but also outperform the classification methods using other types of supervised classifiers after our proposed iterative convolutional neural network.

/pdf/human-activity-classification-with-radar-optimization-and-367collsiu.pdf

Human Activity Classification With Radar: Optimization and Noise Robustness With Iterative Convolutional Neural Networks Followed With Random Forests

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Inverse Synthetic Aperture Radar Imaging with MATLAB® Algorithms: With Advanced SAR/ISAR Imaging Concepts, Algorithms, and MATLAB® Codes

Studies indicate that vertical axis wind turbines provide a more reliable energy conversion technology, as compared to horizontal axis wind turbines, especially in areas of lowly rated and/or uncertain wind speeds. The challenge however is the development of an efficient Savonius rotor blade which is affordable to low income earners in Kenya. The author researched on different technical design solutions and their advantages in terms of noise, shadows and impacts on birds and wildlife. The objectives of this research were thus to design and develop a Savonius rotor blade locally with locally availlable materials and compare its performance and production cost with the existing blades. The blades were made using glass reinforced fibre because of the light weight of the material which enables it to rotate at very low wind speed, it is also long lasting and does not rot hence can survive in all weather conditions. A prototype was made and after testing and understanding it, a more efficient rotor blade was made. Laboratory and field tests were then done. From the developed blade, a laboratory test was conducted using an industrial fan which could go at a maximum speed of 960 revolutions per minute (RPM) which was calibrated to generate an equivalent wind speed of 15 m/s (meters per second). A torque of 367.57 NM (Newton-metre) at a wind speed of 13.7 m/s was obtained. When the blade was connected to a three phase generator, the line voltages obtained were: 7.5, 8.5, and 8.1 V for line L1, L2 and L3 respectively. The Vac from the generator was then rectified by a bridge rectifier and a maximum voltage obtained was 10.5 Vdc which was then used to charge a 12 V dc lead battery. The battery was fully charged after 11 hours, 36 minutes and used to light a 12Vdc bulb for 7 hours. A field test was also done at Ngong hills at a height above the sea level of 2460m (8070 ft) and a maximum wind speed of 6.44 m/s was reached at the time of testing. The angular velocity obtained was 13.58rads/sec, voltage of 5.63V, 6.2V and 5.93V was recorded for each line. The above laboratory test led to a conclusion that it was possible to locally develop a wind conversion technology that is affordable, efficient and adaptable for Kenya’s average wind speed of 4m/s.

Design and testing of an efficient savonius wind turbine’s rotor blade for low wind speed applications.

In the last two decades, an increase in large rotary machines/systems has been witnessed. To ensure safe operation of these systems especially due to extreme stress caused by centrifugal forces as well as the wind or water loadings, regular structural health monitoring (SHM) of the unbalanced parameters, particularly at the blade tips is necessary. For this, the use of non-contact sensors provides the most appropriate approach; however, millimetric out-of-plane deflection monitoring using non-contact sensors at distances >1 m has not been comprehensively addressed for rotary systems, like wind turbines. This study presents a modelling environment to simulate radar returns to analyse rotary systems. Employing Sammon mapping as a dimensionality reduction procedure in conjunction with 2D visualisation, the study demonstrates the characterisation of dynamic deflection parameters using a fast, portable ground-based interferometric radar (GBR). Comparisons between the GBR results with those of a Leica AR20 GPS indicate a divergence ±12.79 mm. The study utilises SHM framework to acquire, normalise, extract, and validate GBR signals within an SHM framework for structures under test or for deflection validation of the new system. Further, it contributes to the non-contact structural fatigue damage detection during design, testing, and operating stages of rotary structures blade tips.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2019.0503

Deflection characterisation of rotary systems using ground-based radar

Many previous studies have utilized the advantages of GPS for structural health monitoring however high data rate (higher than 1 Hz) is required for structures’ vibration detection using GPS. This paper investigates the advantages of utilizing high-rate satellite clock in a kinematic PPP processing strategy specifically applied to the detection of bridge displacement. Global distributed IGS stations high rate observations were used for GPS satellite clock estimations. The Uncalibrated Phase Delay (UPD) and the Zenith Total Delay (ZTD) parameters were firstly estimated using PPP in static mode. The GPS satellite clock product with 1 Hz sampling rate were successfully estimated by applying the UPD and tropospheric delays as compensations to the carrier phase. The deformation of the suspension cables (20 Hz datasets) and towers (10 Hz datasets) were estimated using both the kinematic PPP, using the 1 s, 30 s, 300 s clocks, and the DD data processing method. The 1 s GPS satellite clock gave the most precise and stable solution when compared with the 30 s and 300 s clocks obtained from IGS. Correlation coefficient of PPP solution and DD solution reflects bridge displacement waveform using 1 s PPP is more consistency and accuracy. The 1 s PPP is an alternative method for suspension cable bridge deflection determination, particular in the scenario that DD is impossible due to failure of reference station.

Xu Tang

Papers

Deflection characterisation of rotary systems using ground-based radar

Suspension Cable Bridge Deflection Determination Using Kinematic PPP with High-Rate GPS Satellite Clock Corrections