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The effect of pulse repetition frequency for the continuous wave radar. (a) Continuous wave radar transmitted signal. (b) Received signal (echo + noise), no attenuation. (c) Recovery signal from received signal by matched filter.
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This paper analyzes noise reduction using matched filter and wavelet transform in the signals of continuous wave radar and pulse radar. The denoising application of wavelets has been used in spectrum cleaning of atmospheric radar signals. Matched filter has a strong anti-noise ability; it can also achieve accurate pulse compression in a very noisy...
Contexts in source publication
Context 1
... SNR is defined as the ratio of the signal power to the noise power in the entire period. The fol- lowing parameters are assumed: sampling frequency = 10 GHz, pulse duration = 8 ns, pulse repetition frequency = 0.24 GHz for the pulse radar ( Figure 2) and transmit- ted frequency = 10 GHz for the continuous wave radar (Figure 3) The receiver receives the return from the targets in the present of AWGN. ...
Context 2
... the pulse radar, the recovery signal is almost similar to transmitted signal shown in Figure 2c. But in the case of continuous wave radar, it is almost impossible to understand the shape of the transmitted signal from the recovery signal (Figure 3). Figures 4 and 5 are similar to Figures 2 and 3, respect- ively, except the received signals are attenuated more than 90%. Figure 4 indicates that the matched filter has a strong advantage in anti-noise ability for pulse radar. ...
Context 3
... 7c shows the noise reduction by traditional wavelet for con- tinuous wave radar. By comparing this with Figure 3c, we can say that more noise is reduced in Figure 7c. Figure 8c shows the improvement in noise reduction by our proposed method. The reason for this is that the SNR is increased (Table 1) when we use the wavelet denoising technique for continuous wave radar. ...
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... Figure 2 is the flowchart of ultrasound echo signal processing, where ( ) is the noise-free echo signal, ( ) is Gaussian white noise with a mean of 0, and the bilateral power spectral density is ; r(t) is the signal to be processed, ( ) is the filter frequency response, and ( ) is the output signal. If the maximum output signal-to-noise ratio criterion is adopted, the matched filter is the corresponding filter [46]. The derivation of the matched filter is relatively complicated, and the final conclusion will be given here directly. ...
Originating in the early 20th century, ultrasonic testing has found increasingly extensive applications in medicine, industry, and materials science. Achieving both a high signal-to-noise ratio and high efficiency is crucial in ultrasonic testing. The former means an increase in imaging clarity as well as the detection depth, while the latter facilitates a faster refresh of the image. It is difficult to balance these two indicators with a conventional short pulse to excite the probe, so in general handling methods, these two factors have a trade-off. To solve the above problems, coded excitation (CE) can increase the pulse duration and offers great potential to improve the signal-to-noise ratio with equivalent or even higher efficiency. In this paper, we first review the fundamentals of CE, including signal modulation, signal transmission, signal reception, pulse compression, and optimization methods. Then, we introduce the application of CE in different areas of ultrasonic testing, with a focus on industrial bulk wave single-probe detection, industrial guided wave detection, industrial bulk wave phased array detection, and medical phased array imaging. Finally, we point out the advantages as well as a few future directions of CE.
... Various denoising methods have been developed for the radar signal, such as wavelet denoising, match filter, adaptive filter, and high-resolution spectral analysis [15][16][17], and they are investigated at length in textbooks and lecture notes [18][19][20]. However, it is still an open question about designing an effective denoising method for resource-constrained platforms for measured data without a clean reference and how denoising contributes to classification accuracy. ...
Radar‐based human activity recognition is considered as a competitive solution for the elderly care health monitoring problem, compared to alternative techniques such as cameras and wearable devices. However, raw radar signals are often contaminated with noise, clutter, and other artifacts that significantly impact recognition performance, which highlights the importance of prepossessing techniques that enhance radar data quality and improve classification model accuracy. In this study, two different human activity classification models incorporated with pre‐processing techniques have been proposed. The authors introduce wavelet denoising methods into a cyclostationarity‐based classification model, resulting in a substantial improvement in classification accuracy. To address the limitations of conventional pre‐processing techniques, a deep neural network model called Double Phase Cascaded Denoising and Classification Network (DPDCNet) is proposed, which performs end‐to‐end signal‐level classification and achieves state‐of‐the‐art accuracy. The proposed models significantly reduce false detections and would enable robust activity monitoring for older individuals with radar signals, thereby bringing the system closer to a practical implementation for deployment.
... where R f is often referred to as Matched-Filter [32,33]. Thus, we have ...
Time-frequency analysis in waveform engineering can be applied to many detection and imaging systems, such as radar, sonar, and ultrasound to improve their Signal-to-Noise Ratio (SNR). Recently, photoacoustic imaging systems have attracted researchers’ attention. However, the SNR optimization problem for photoacoustic systems has not been fully addressed. In this paper, the one-dimensional SNR optimization of the photoacoustic response to an input waveform with finite duration and energy was considered. This paper applied an eigenfunction optimization approach to find the waveform for optimal SNR for various photoacoustic absorber profiles. SNR gains via the obtained optimal waveform were compared with simple square-pulse and pulsed sinusoidal waveforms in simulations. Results showed that by using the optimal waveform, SNR can be enhanced especially if the input wave duration is comparable with the absorber time profile duration. The optimal waveforms can achieve 5–10% higher SNR than square pulses and over 100% higher SNR compared with pulsed sinusoids. The symmetry between time and frequency domains assures similar behavior when temporal durations of the input waveforms are too short or too long compared with the absorber.
... Si bien, la relación entre la distancia y el retardo es muy simple, medir el valor de en forma directa no es una tarea sencilla [2], pues ello requiere no solo una gran velocidad de procesamiento del dispositivo que captura las señales, sino del uso de métodos muy sofisticados de sincronismo, filtraje y decisión basada en umbrales, que permitan medir con una exactitud aceptable el retardo del eco [3], [4]. ...
En este artículo proponemos una estimación de distancia simple soportada en un sistema de radar de pulso. El método consiste en enviar señales periódicas formadas a partir de una familia wavelet ortogonal y la medida del atraso del eco producido por el albo e un dominio diferente al temporal. Los resultados de las simulaciones muestran una precisión aceptable en la determinación de la distancia, evitando los métodos complejos de sincronización, filtrado y decisión, utilizados en radares de pulso tradicionales
... [141], [168], [169] and [170] work with raw radar signals in the frequency domain. Baili et al. [168] work with ground penetrating radar. ...
... The chirplet transform makes it possible to extract clean signal parameters and use them to remove the noise. Islam and Chong [170] analyze noise reduction using matched filter and wavelet transform in the signals of continuous wave radar and pulse radar. Islam and Chong find that matched filter has a strong anti-noise ability for pulse radar and wavelet for continuous wave radar. ...
... ResNeXt [101] NASNet [102] EfficientNet [103] R-CNN [107] SSD [112] YOLO [108] YOLOv2 [109] YOLOv3 [76] RetinaNet [64] RefineDet [113] TridentNet [114] PointNet [85] PointNet++ [43] PointCNN [115] KPConv [118] Ψ-CNN [119] OctNet [120] O-CNN [121] Andina and Sanz-González [124] Zyweck and Bogner [125] Cheikh and Faozi [126] Heuel and Rohling [127] Angelov et al. [128] Wohler et al. [122] Schumann et al. [42] Dube et al. [129] Lombacher et al. [130] Lombacher et al. [131] Lombacher et al. [179] Lombacher et al. [1] Danzer et al. [133] Schlosser et al. [136] AVOD [137] Bijelic et al. [32] Ji and Prokhorov [138] Chadwick et al. [51] Chollet [56] Zhang et al. [149] Chen et al. [140] Zhao et al. [151] Godard et al. [152] Dimitrievski et al. [159] Roveri et al. [157] Väänänen [158] Hermosilla et al. [167] Islam and Chong [170] Gradolewski et al. [169] 3 State of the Art Table 3.3 -continued from previous page Work Modality Task C a m e r a L id a r a n d 3 -D p o in t c lo u d R a d a r F il t e r in g a n d r e s t o r a t io n C la s s ifi c a t io n D e t e c t io n S e g m e n t a t io n ...
Autonomous vehicles are safety critical systems and require a very high level of reliability. By combining technologies that rely on different physical principles and types of information, the perception can be superior in terms of reliability, accuracy, computational time and costs. Thus, the given task is to develop a software for environmental perception based on automotive camera and radar sensors.
The topic of this master’s thesis is two-folded. On the one hand, state-of-the-art radar and camera sensors are to be fused and used for object detection via neural networks. On the other hand, false positive detections from radar sensors are to be filtered via neural networks. For the entire work, real data from state-of-the-art sensors are being used. The results are evaluated on the publicly available nuScenes dataset. The performance of the radar fusion network is evaluated against an image only approach.
The following work packages have been done:
1. Familiarization with the state of the art of neural filtering, sensor data fusion and object detection.
2. Analyzing the radar data for relevant properties.
3. Developing a neural fusion network for object detection based on camera and radar.
4. Developing a neural filter network for filtering automotive radar data.
5. Investigating different detection performances from raw-data fusion to object-level fusion.
6. Investigating the impact of different preprocessing methods.
7. Evaluating all aspects on real automotive sensor data.
... The correlation receiver and/or the matched filter is applied not only in the RFID technology but also in many other areas of the communication systems such as the radiolocation and the mobile communications. The reduction in noise by the matched filter is described in the study by Islam and Chong, 24,25 but in these papers the main application is focused on the pulse and continuous wave radars. The authors performed comparison of the matched filter and the wavelet transformation properties in noise reduction. ...
The radiofrequency identification (RFID) technology is widely used in modern industry to identify and localize the final manufactured products and their parts. This article analyses and optimizes the localization process of special RFID transponders – markers used to mark the position and type of the underground facility networks (pipes, cables, etc.). The analysis of electric circuits representing the system consisting of the marker and the localization device is performed by numerical solution of the corresponding equations. The results of the numerical solution are then used for calculation of the analytical description of the waveform received as response from the excited marker. The constants obtained from the analytical form of the solution are then used as input parameters for optimization of time window width in the correlation receiver of the marker responses. The optimization is focused on the maximization of the signal-to-noise ratio in the receiving time window. The theoretical calculations are completed by the processing of real signals recorded by an oscilloscope from the localization device where the correlation receiver is planned to apply.
... The problems with noise in UHF RFID is studied in [7] where the authors measure a distribution of signal-to-noise ratio by using software defined radio receiver. The reduction of noise by the matched filter is described in [8] and [9], but in these papers the main application is focused on the pulse and continuous wave radars. The authors perform comparison of the matched filter and the wavelet transformation properties in noise reduction. ...
The actual applications of the radiofrequency identification (RFID) systems in industry are focused not only on the identification but also on the localization of the RFID transponders. The special type of the RFID transponders is used to localize and to identify the underground facility networks such as pipes and cables. In such applications the RFID transponders are called markers. The paper describes an analysis of the correlation receiver for RSSI based localization of the inductive coupled RFID markers. The analysis is performed by the modeling of the localization device and the marker in Matlab – Simulink software. The aim of the analysis is to examine the ability of the correlation receiver to suppress the interfering signals from industrial sources, for example from the long wave telemetry transmitters which have their working frequencies in the same band as the working frequencies of the markers.
... Various advanced methods of noise suppression in a Doppler sensor were proposed. For example, Islam and Chong used a matched filter and wavelet analysis [7]. This paper proposes an alternative approach to suppression of noise and electromagnetic interferences in the Doppler sensor signal. ...
... (iii) They are inherently anti-jam and interference resistant; and finally (iv) Chaotic signals are spectrally very efficient and can share spectral bands without mutual interference. Therefore, chaotic radar may em ploy coherent signal processing schemes either by matched filter or correlation to reduce the noise and eventually obtain the highest enhancement in signal-to-noise ratio (SNR) [4] [24]. ...
Although the Very Low-Frequency (VLF) waveforms have limited practical applications in acoustics (sonar) and secure military communications with radars and submarines; to this end; this paper presents a new and simple analytical model of VLF monostatic direct chaotic radar system. The model hypothetically depends on the two identical coupled time-delayed feedback chaotic systems which can generate and recover a long-wave chaotic signal. To resist the influence of positive Lyapunov exponents of the time-delay chaotic systems, the complete replacement of Pecaro and Carroll (PC) synchronization is employed. It can faithfully recover the chaotic signal from the back-scattered (echo) signal from the target over a noisy channel. The system performance is characterized in terms of the time series of synchronization in addition to the peak of the cross-correlation. Simulation results are conducted for substantial sensitivities of the chaotic signal to the system parameters and initial conditions. As a result, it is found that an effective and robust chaotic radar (CRADAR) model can be obtained when the signal-to-noise ratio (SNR) highly degrades to 0 dB, but with clear peak in correlation performance for detecting the target. Then, the model can be considered as a state of the art towards counter stealth technology and might be developed for other acoustic secure applications.
... As traditional soft thresholding and hard thresholding have limitations as mentioned in Sect. 2.2, we have proposed modified threshold function [24]. The Eq. (3) shows the modified threshold function that not only overcomes the shortcoming of hard thresholding and soft thresholding but also improves the reconstruction precision since it reduces the constant errors. ...
One of the main limitations of existing monitoring systems is their dependency on the continuous recording of video data. As a result, the system consumes huge power and needs large memory to store this data. The aim of this paper is to present an automated monitoring system that can save memory, as well as measure the target distance precisely based on the motion sensors and ultrasonic sensor. The target is detected by motion sensors and then an ultrasonic sensor is used to measure the target distance. The cross-correlation technique is used to calculate the distance of targets using ultrasonic signal. To obtain high measuring accuracy, noise reduction technique and temperature effect on velocity have been adopted. A series of real-world experiments are conducted with different targets and target positions. The experimental results show that using a noise reduction technique and temperature compensation improve the accuracy of the designed system.
