Pulse Compression Method Research Articles

Microwave computational imaging in frequency domain with reprogrammable metasurface

Recently, microwave computational imaging systems have had various applications ranging from security screening to biomedical diagnosis. However, existing methods are sensitive to noise and have a heavy computational burden in a three-dimensional (3-D) imaging scene. A computational imaging method approached in frequency domain is proposed, which improves imaging quality under noisy conditions and reduces computation complexity. The signal-to-noise ratio of the echo signal is improved by dechirping pulse compression method, which obtains the range resolution concurrently. According to the information of range resolution, the scene is divided into some range bins. With computational imaging algorithms, the azimuth and elevation resolution are obtained in each range bin by spatially diverse patterns of reprogrammable metasurface. A sparse 3-D image can be obtained by combining the reconstructed subimages. The simulation result shows that the proposed method outperforms the conventional methods with better antinoise ability and lower computational complexity in sparse 3-D scene imaging.

A novel sidelobe cancellation method for Barker code pulse compression

Barker Phase coded signals are one of the most effective technique used in pulse compression radars. The main problem of using these signals is the existence of sidelobes at the output of the matched filter. These sidelobes mask nearby weak targets. Also, it degrades the overall detection performance. In the present work, a novel method to totally remove these sidelobes is presented rather than conventional sidelobes reduction methods. The superior of the proposed method is evaluated through the Receiver Operation Characteristic (ROC) curve and simulated in case of single or multiple targets scenarios.

Free-beam soliton self-compression in air

We identify a physical scenario whereby soliton transients generated in freely propagating laser beams within the regions of anomalous dispersion in air can be compressed as a part of their free-beam spatiotemporal evolution to yield few-cycle mid- and long-wavelength-infrared field waveforms, whose peak power is substantially higher than the peak power of the input pulses. We show that this free-beam soliton self-compression scenario does not require ionization or laser-induced filamentation, enabling high-throughput self-compression of mid- and long-wavelength-infrared laser pulses within a broad range of peak powers from tens of gigawatts up to the terawatt level. We also demonstrate that this method of pulse compression can be extended to long-range propagation, providing self-compression of high-peak-power laser pulses in atmospheric air within propagation ranges as long as hundreds of meters, suggesting new ways towards longer-range standoff detection and remote sensing.

Study on a Quantitative Analysis Method for Pulse Compression Results

In order to further improve the ability of detecting and evaluating the detection performance and interference effect of the integrated signal, a quantitative analysis method (K-means quantization) for pulse compression is proposed. The method is based on the amplitude analysis of the pulse compression results. By using the improved K-means clustering method, the recognition degree of the selected target points is obtained by induction and analysis. The simulation results show that the analysis of the detection performance or interference performance of the integrated signal is consistent with the traditional analysis conclusion by using K-means quantization method. It has better measurability, objectivity and independence, which can be used for automatic evaluation of the system..

Adaptive Pulse Compression Technique for X-Band Phased Array Weather Radar

Weather radar commonly uses a matched filter (MF) method to improve the range resolution and signal-to-noise ratio. A X-band phased array weather radar (PAWR), which is capable of 3-D precipitation observations in less than 30 s, is in operation at the Osaka University. The PAWR uses the MF method. In weather radar systems, the magnitude of the range sidelobes is an important topic because it can cause overestimation of the received power from a target, such as precipitation or ground clutter echoes. We propose a minimum mean square error (MMSE)-based pulse compression method to reduce the range sidelobes of the PAWR. We evaluated an MF, an MF with a raised-cosine window, and MMSE methods using numerical simulations and actual measurement data obtained from the PAWR. The results show that the MMSE method is clearly superior to the MF and MF with a raised-cosine filter methods when considering the reduction in the range sidelobes.

A New Dynamic Complex Baseband Pulse Compression Method for Chirp-Coded Excitation in Medical Ultrasound Imaging.

Chirp-coded excitation can increase the signal-to-noise ratio (SNR) without degrading the axial resolution. Effective pulse compression (PC) is important to maintain the axial resolution and can be achieved with radio frequency (RF) and complex baseband (CBB) data (i.e., and , respectively). can further reduce the computational complexity compared to ; however, suffers from a degraded SNR due to tissue attenuation. In this paper, we propose a new dynamic CBB PC method ( that can improve the SNR while compensating for tissue attenuation. The compression filter coefficients in the method are generated by dynamically changing the demodulation frequencies along with the depth. For PC, the obtained coefficients are independently applied to the in-phase and quadrature components of the CBB data. To evaluate the performance of the proposed method, simulation, phantom, and in vivo studies were conducted, and all three studies showed improved SNR, i.e., maximally 3.87, 7.41, and 5.75 dB, respectively. In addition, the measured peak range sidelobe level of the proposed method yielded lower values than the and , and it also derived a suitable target location, i.e., a <0.07-mm target location error, while maintaining the axial resolution. In an in vivo abdominal experiment, the method depicted brighter and clearer features in the hyperechoic region because highly correlated signals were produced by compensating for tissue attenuation. These results demonstrated that the proposed method can improve the SNR of chirp-coded excitation while preserving the axial resolution and the target location and reducing the computational complexity.

Air-Coupled Ultrasonic Signal Processing Method for Detection of Lamination Defects in Molded Composites

In order to improve signal-to-noise ratio (SNR) of air-coupled ultrasonic signal in the detection of lamination defects in molded composite, the pulse compression and wavelet filtering hybrid signal processing method is proposed. The selection principle of parameters of the hybrid signal processing method is studied. The actual detection results of molded composite show that the hybrid method is very effective in improving the SNR of air-coupled ultrasonic signal when selecting reasonable parameters (The experiment results demonstrate that the optimal parameters are 13-bit Barker code sequences signal with three-cycle per sub-pulse, db9 wavelet, six decomposition levels, and soft threshold function.). An improvement in SNR up to 18.81 dB is attained compared with the original received signal. The quantitative accuracy of defects in C-scan image based on the hybrid method is also very high, and defects as small as $$\emptyset $$ 5 mm can be easily identified.

Oversampled Pulse Compression Based on Signal Modeling: Application to CONSERT/Rosetta Radar

The context of space missions implies very strong constraints on the design of the instruments. For instance, mass, data rates, power consumption, clock frequency, and accuracy are very limited. These limitations degrade the performance and the accuracy of the measurements. This paper is related to the study of signals sampled at a low frequency. More exactly, we propose an oversampled pulse compression method for radar signals, which allows to reconstruction the signals with a much higher sampling rate. Consequently, this method allows significantly improving the multipath amplitude and the delay estimation accuracy. The efficiency of our method is clearly demonstrated with real measurements. These latter correspond to calibration measurements performed on ground with the radar COmets Nucleus Sounding Experiment by Radio-wave Transmission. The latter allows performing the tomography in the transmission of 67P Churyumov–Gerasimenko comets nucleus in the frame of the Rosetta/European Space Agency space mission. The results show that the proposed method allows estimating the delays with accuracy better than 10% of the sampling period in the case of a sampling frequency value close to the Nyquist limit. The analysis of the measured signals shows how a small frequency aliasing power degrades the delay estimation performance. This problem can be resolved using an estimation method based on an end-to-end signal modeling.

Application of P4 Polyphase codes pulse compression method to air-coupled ultrasonic testing systems

Air-coupled ultrasonic testing systems are usually restricted by low signal-to-noise ratios (SNR). The use of pulse compression techniques based on P4 Polyphase codes can improve the ultrasound SNR. This type of codes can generate higher Peak Side Lobe (PSL) ratio and lower noise of compressed signal. This paper proposes the use of P4 Polyphase sequences to code ultrasound with a NDT system based on air-coupled piezoelectric transducer. Furthermore, the principle of selecting parameters of P4 Polyphase sequence for obtaining optimal pulse compression effect is also studied. Successful results are presented in molded composite material. A hybrid signal processing method for improvement in SNR up to 12.11dB and in time domain resolution about 35% are achieved when compared with conventional pulse compression technique.

Multiple-Access Interference Mitigation for Acquisition of Code-Division Multiple-Access Continuous-Wave Signals

Multiple-access interference mitigation is important in code-division multiple-access (CDMA) systems for both information recovery and signal acquisition. Therefore, in this letter, we propose an open-loop adaptive filter based on the reiterative minimum mean-square error for the acquisition of CDMA signals. The method is based on the existing multistatic adaptive pulse compression method, appropriately adapted to the characteristics of CDMA continuous-wave signals. The efficacy of the proposed method in such systems is verified by simulation, and its superiority when compared with the existing least-mean-square method in terms of the number of reiterations is established.

Fast cross-correlation mitigation via minimum mean-square error estimation based on matched filter outputs for consecutive DSSS signals

In the direct sequence spread spectrum (DSSS) system, multiple-access interference mitigation is critical to improving the acquisition performance. Therefore, in this paper, a fast cross-correlation mitigation algorithm based on the minimum mean-square error criterion is proposed. The algorithm exploits the matched filter outputs; hence, it is applicable to existing DSSS receivers based on direct pseudorandom noise code correlation. Essentially, the proposed scheme is an adaptive filter that optimizes each individual uncertain code phase delay. The algorithm employs both the code sequence information of the desired signal and that of the multiple-access interference signal, which enables it to outperform the standard matched filter, conventional least-mean-squares algorithm, and the pulse compression repair method. Furthermore, the proposed algorithm decreases the computational load compared with the existing multistatic adaptive pulse compression method by reducing the stage-number of the adaptive filter; this results in a slight degradation in performance. Numerical results verify the validity of the proposed algorithm.

Adaptive Pulse Compression of MIMO Radar in Food Density Measurement Based on Infinite Norm Normalization

This study presents MIMO radar in food density measurement signal separation method-INN-LCMV adaptive pulse compression method based on Linear Constrained Minimum Variance (LCMV) criterion and infinite norm normalization method. In the presented method, unrequited transmit signal and non-Gaussian noise are regarded as interference, the received signals are processed in the infinity norm normalization method, the weight coefficients of the filter based on the linear constrained minimum variance are derived. The simulation results show that, this method is suitable for the non-Gaussian noise, the influence of noise on signal separation performance is relatively small, the proposed method is very efficient for MIMO radar in food density measurement signal separation in non-Gaussian noise.

Few-cycle laser pulses generation with frequency tuning in a molecular gas-filled hollow-core fiber.

We study theoretically a pulse compression method with gas-filled hollow-core fiber based on ultrafast molecular phase modulation. The simulation results show the molecular phase modulation can impart a positive or negative chirp on probe pulse and tune the central wavelength by changing the time delay between the pump and probe pulses. This approach is demonstrated to be suitable for generation of frequency-tunable few-cycle pulses with a smooth spectrum.

Pulse compression and dispersion compensation for high- resolution Lamb wave inspection

The dispersion of ultrasonic guided waves causes the energy of a signal to spread out in space and time as it propagates, which decreases the performance for damage detection significantly. A lot of signal processing methods have been proposed to reduce the effect of dispersion for this reason. In this paper, with the aim of developing an efficient methodology for high resolution Lamb wave inspection, a pulse compression and dispersion compensation method is established. In this method, broadband excitation and pulse compression technique are introduced to reconstruct the transform function with a high SNR. Subsequently, a scheme is established to alleviate the dispersion effects by performing compensation on the original narrowband excitation signals, and thus the time duration of received wave packet can be compressed during the extracting process. Finally, Numerical simulation and experiment are carried on aluminum specimens to investigate the behavior of the proposed method.

단거리 차량용 초광대역 레이더 송신기의 스펙트럼 분석

In this paper, we propose structures and power spectral densities of UWB radar transmitters of Short Range Automobile. While the conventional transmitters did not consider interferences from self and other automobiles, the proposed method of this paper can minimize interferences. First, we compare a structure of the proposed method with pulse train and pulse compression method. Then, by using mathematical analysis and computer simulations, we show that the proposed method is superior to others. Also we can set proper parameters in UWB radar's transmitter through the numerical method of mathematical results.

Laser pulse compression method to measure Brillouin gain in water

We present a method by which to determine the gain coefficient of stimulated Brillouin scattering (SBS) in water from the pulse compression ratio of the pump pulse duration to the output Stokes pulse duration. To achieve this objective, we have measured the pulse duration of SBS over the temperature range of 5–40 °C. The gain coefficient of SBS has been calculated using the measured pulse compression ratio, the pump intensity, and the characteristic length. Also, in this article, we derive the theoretical model based on coupled wave equations and we demonstrate the method at lower pump energies which is an effective approach for measuring the gain coefficient of SBS.

A real-time chirp-coded imaging system with tissue attenuation compensation

In ultrasound imaging, pulse compression methods based on the transmission (TX) of long coded pulses and matched receive filtering can be used to improve the penetration depth while preserving the axial resolution (coded-imaging). The performance of most of these methods is affected by the frequency dependent attenuation of tissue, which causes mismatch of the receiver filter. This, together with the involved additional computational load, has probably so far limited the implementation of pulse compression methods in real-time imaging systems.In this paper, a real-time low-computational-cost coded-imaging system operating on the beamformed and demodulated data received by a linear array probe is presented. The system has been implemented by extending the firmware and the software of the ULA-OP research platform. In particular, pulse compression is performed by exploiting the computational resources of a single digital signal processor. Each image line is produced in less than 20μs, so that, e.g., 192-line frames can be generated at up to 200fps.Although the system may work with a large class of codes, this paper has been focused on the test of linear frequency modulated chirps. The new system has been used to experimentally investigate the effects of tissue attenuation so that the design of the receive compression filter can be accordingly guided. Tests made with different chirp signals confirm that, although the attainable compression gain in attenuating media is lower than the theoretical value expected for a given TX Time-Bandwidth product (BT), good SNR gains can be obtained. For example, by using a chirp signal having BT=19, a 13dB compression gain has been measured. By adapting the frequency band of the receiver to the band of the received echo, the signal-to-noise ratio and the penetration depth have been further increased, as shown by real-time tests conducted on phantoms and in vivo. In particular, a 2.7dB SNR increase has been measured through a novel attenuation compensation scheme, which only requires to shift the demodulation frequency by 1MHz. The proposed method characterizes for its simplicity and easy implementation.

Parameter optimization of pulse compression method in air-coupled ultrasonic testing

Parameter optimization of pulse compression method in air-coupled ultrasonic testing

Two-Dimensional Imaging Algorithm Based on Linear Prognosis for Space Target in Bistatic ISAR System

In bistatic inverse synthetic aperture radar (Bi-ISAR) system, its image resolution is lower than monostatic ISAR system. In order to solve this problem, the linear prognosis algorithm is adopted in the imaging process and the imaging algorithm based on linear prognosis is proposed. Space target Bi-ISAR imaging is taken as example in the research. The one-dimensional range profile is created through pulse compression method. Before the azimuth compression, burg entropy maximum algorithm in Levions recursive method is used to estimate the prognosis coefficients and the azimuth echo data. Then Fourier transformation is used to compress the azimuth data in order to get the high resolution azimuth image. This imaging method can obtain the two-dimensional image with the resolution equal to the monostatic ISAR or even higher than it. Simulation experiments have verified the effectiveness and availability of the algorithm.

A Pulse Compression Waveform for Improved-Sensitivity Weather Radar Observations

AbstractThe progression of phased array weather observations, research, and planning over the past decade has led to significant advances in development efforts for future weather radar technologies. However, numerous challenges still remain for large-scale deployment. The eventual goal for phased array weather radar technology includes the use of active arrays, where each element would have its own transmit/receive module. This would lead to significant advantages; however, such a design must be capable of utilizing low-power, solid-state transmitters at each element in order to keep costs down. To provide acceptable sensitivity, as well as the range resolution needed for weather observations, pulse compression strategies are required. Pulse compression has been used for decades in military applications, but it has yet to be applied on a broad scale to weather radar, partly because of concerns regarding sensitivity loss caused by pulse windowing. A robust optimization technique for pulse compression waveforms with minimalistic windowing using a genetic algorithm is presented. A continuous nonlinear frequency-modulated waveform that takes into account transmitter distortion is shown, both in theory and in practical use scenarios. Measured pulses and weather observations from the Advanced Radar Research Center’s dual-polarized PX-1000 transportable radar, which utilizes dual 100-W solid-state transmitters, are presented. Both stratiform and convective scenarios, as well as dual-polarization observations, are shown, demonstrating significant improvement in sensitivity over previous pulse compression methods.