Pulse Compression Properties Research Articles

LPI Radar Waveform Design With Desired Cyclic Spectrum and Pulse Compression Properties

This paper considers the practical LPI radar waveform design problem for jointly achieving a desired cyclic spectrum and pulse compression properties. In this work, the weighted cyclic frequency sidelobe (WCFS) level is minimized to achieve the LPI purpose while the similarity constraint regarding a known radar waveform that occupies the desired detection properties is considered. The waveform design problem is then formulated as a quartic optimization problem with heterogeneous quadratic inequality constraints. These properties make the problem NP-hard in general. To solve this problem efficiently, by introducing necessary auxiliary variables, the original problem is converted into several quadratic optimization problems with respect to each independent variable under a separated linear inequality constraint, which can be efficiently solved by leveraging the alternation direction method of multipliers (ADMM) framework. Finally, the performance of the proposed method is demonstrated via numerical examples.

Robust radar waveform design for extended targets with multiple spectral compatibility constraints

We address the robust radar waveform design for extended target detection. To achieve excellent spectral compatibilities and pulse compression properties, the multiple Spectral Compatibility Constraints (SCC) and Similarity Constraint (SC) are imposed on the waveform. The goal is to maximize the worst-case Signal-to-Interference-pulse-Noise Ratio (SINR) at the receiver against the spherical uncertainty of Target Impulse Response (TIR), resulting in a non-convex max-min optimization problem which is Non-Polynomial (NP) hard in general. Leveraging on the Successive Upper-bound Minimization (SUM) techniques, we devise two algorithms to find high qualified waveforms. The convergences of the proposed algorithms are analyzed theoretically. The effectivenesses of the proposed algorithms are verified by numerical experiments. Simulation results highlight that, compared with the current waveform, the waveform designed by the proposed algorithms not only enjoys the excellent spectral compatibilities and pulse compression properties, but also shows robustness against the uncertainty of TIR.

Probability of detection of deep defects in steel samples using Barker coded independent component thermography

Barker coded independent component thermography (BCICT) approach known for exploiting the pulse compression properties with independent component analysis method was used to examine a mild steel sample with drilled flat-bottomed holes at various depths. This Letter emphasises the application of the probability of detection (POD) as a predictive assessment tool for the efficacy of the different methods to detect the defects at varying depths. The results exhibited that the aspect ratio of the deep defect r 90 with 90% POD and r 90 / 95 for 90% POD with 95% confidence that can be detected using the BCICT approach are 3.161 and 3.835, respectively. Besides, a relation between the POD of the defect at different depths as a feature of the defect aspect ratio (diameter/depth) has also been presented.

Communication-Aware Waveform Design for MIMO Radar With Good Transmit Beampattern

Designing the radar waveform, which ensures spectral compatibility with the communication systems, is known to be challenging. In addition to having the desirable transmitter efficiency, it is also anticipated to share the good pulse compression property of the reference waveform. In this paper, we investigate the problem of waveform design for multiple-input multiple-output radar with good transmit beampattern under certain practical constraints (e.g., peak to average power ratio and similarity constraints) in coexistence with communication systems. The waveform is designed by minimizing a weighted summation of the beampattern integrated sidelobe-to-mainlobe ratio and waveform energy over the space-frequency bands. Since the resulting problem is NP-hard, two approximated primal-dual algorithms based on the alternating direction method of multipliers algorithm are proposed. Concretely, the proposed algorithms update the primal variable by minimizing the linearized and quadratic approximations of the augmented Lagrangian function of the original problem, respectively. The closed-form solution of each primal variable is provided. Moreover, both the convergence and computational complexities of these two algorithms are discussed. Numerical simulations are provided to demonstrate the effectiveness of the proposed approaches.

Multibeam radar based on linear frequency modulated waveform diversity

Multibeam radar (MBR) systems based on waveform diversity require a set of orthogonal waveforms in order to generate multiple channels in transmission and extract them efficiently at the receiver with digital signal processing. Linear frequency modulated (LFM) signals are extensively used in radar systems due to their pulse compression properties, Doppler tolerance, and ease of generation. Here, the authors investigate the level of isolation between MBR channels based on LFM chirps with rectangular and Gaussian amplitude envelopes. The orthogonal properties and the mathematical expressions of the isolation are derived as a function of the chirp design diversity, and specifically for diverse frequency slopes and frequency offsets. The analytical expressions are validated with a set of simulations as well as with experiments at C-band using a rotating target.

MIMO Radar Waveform Design With PAPR and Similarity Constraints

The paper investigates the joint design of transmit waveform and receive filter for multiple-input multiple-output radar in the presence of signal-dependent interference, subject to a peak-to-average-power ratio constraint as well as a waveform similarity constraint. Owing to this kind of signal dependence and constraints, the formulated optimization problem of the output signal-to-interference-plus-noise ratio (SINR) maximization is NP-hard. To this end, an auxiliary variable is first introduced to modify the original problem, and then a primal-dual algorithm based on the block successive upper-bound minimization method of multipliers (BSUM-M) is developed to deal with the resulting problem. Moreover, an active set method is exploited to solve the quadratic programming problem involved in each update procedure of the proposed BSUM-M algorithm. Finally, numerical simulations are performed to demonstrate the superiority of the proposed algorithm over state-of-the-art methods in terms of the output SINR, beampattern, computational complexity, pulse compression, and ambiguity properties.

BARKER-CODED NODE-PORE RESISTIVE PULSE SENSING WITH BUILT-IN COINCIDENCE CORRECTION.

A resistive pulse sensing device is able to extract quantities such as concentration and size distribution of particles, e.g. cells or microspheres, as they flow through the device's sensor region, i.e. channel, in an electrolyte solution. The dynamic range of detectable particle sizes is limited by the channel dimensions. In addition, signal interference from multiple particles transiting the channel simultaneously, i.e. coincidence event, further hinder the dynamic range. Coincidence data is often considered unusable and is discarded, reducing the throughput and introducing possible biases and errors into the distributions. Here, we propose a two-step solution. We code the channel such that the system response results in a Manchester encoded Barker-Code sequence, allowing us to take advantage of the code's pulse compression properties. We pose the parameter estimation problem as a sparse inverse problem, which enables estimation of particle sizes and velocities while resolving coincidences, and solve it with a successive interference cancellation algorithm. We introduce modifications to the algorithm to account for device fabrication variations and natural stochastic variations in flow. We demonstrate the ability to resolve coincidences and possible increases in the device's dynamic range by screening particles of different size through a Barker encoded device.

Orthogonal frequency division multiplexing linear frequency modulation signal design with optimised pulse compression property of spatial synthesised signals

Orthogonal frequency division multiplexing (OFDM) linear frequency modulation (LFM) waveform is widely studied due to its application potentials in multiple-input–multiple-output (MIMO) radar, but its effective design is still a challenge. Considering the critical role, the pulse compression property of spatial synthesised signals plays in MIMO radar, a detailed analysis is made using OFDM LFM signals, resulting in the radical reasons for the high grating sidelobes. Then, a joint optimisation method for OFDM LFM signal design based on genetic algorithm and sequential quadratic programming is proposed to degrade the sidelobe level dramatically. Furthermore, to nullify the grating sidelobes thoroughly, a modification is performed through optimising the relaxed frequency steps of the OFDM LFM waveform, which involves a balance between sidelobe property and orthogonality. Numerical results validate the theoretic analysis and show the superior performance of the designed OFDM LFM waveforms in pulse compression properties of spatial synthesised signals.

Successive QCQP Refinement for MIMO Radar Waveform Design Under Practical Constraints

The authors address the problem of designing a waveform for multiple-input multiple-output (MIMO) radar under the important practical constraints of constant modulus and waveform similarity. Incorporating these constraints in an analytically tractable manner is a longstanding open challenge. This is due to the fact that the optimization problem that results from signal-to-interference-plus-noise ratio (SINR) maximization subject to these constraints is a hard non-convex problem. The authors develop a new analytical approach that involves solving a sequence of convex quadratically constrained quadratic programing (QCQP) problems, which they prove converges to a sub-optimal solution. Because an improvement in SINR results via solving each problem in the sequence, they call the method Successive QCQP Refinement (SQR). Furthermore, the proposed SQR method can be easily extended to incorporate emerging requirements of spectral coexistence, as shown briefly in this paper. The authors evaluate SQR against other candidate techniques with respect to SINR performance, beam pattern, and pulse compression properties in a variety of scenarios. Results show that SQR outperforms state-of-the-art methods that also employ constant modulus and/or similarity constraints while being computationally less burdensome.

Binary codes for multirange-resolution radar and pulse-compression properties

We propose new binary codes with various bandwidths for multirange-resolution radar. These spectrums do not have deep valleys over a wide frequency range. A mismatched filter, which consists of a matched filter and a least-error energy-shaping filter, is applied for the pulse compression. It is demonstrated that the pulse-compression loss of the proposed codes is very small compared with the loss of conventional binary codes, even though the proposed codes are compressed to a very narrow pulse width by expansion of the bandwidth.

PULSE COMPRESSION WITH GAUSSIAN WEIGHTED CHIRP MODULATED EXCITATION FOR INFRARED THERMAL WAVE IMAGING

This paper proposes a novel signal processing approach to thermal non-destructive testing by incorporating Gaussian window function onto the linear frequency modulated incident heat ∞ux to achieve better pulse compression properties. The present work highlights a flnite element analysis based modeling and simulation technique in order to test the capabilities of the proposed windowing scheme over the conventional frequency modulated thermal wave imaging method. It is shown that by using Gaussian weighted chirp thermal stimulus, high depth resolution can be achieved.

MIMO Radar Waveform Design With Constant Modulus and Similarity Constraints

We consider the problem of waveform design for Multiple-Input Multiple-Output (MIMO) radar in the presence of signal-dependent interference embedded in white Gaussian disturbance. We present two sequential optimization procedures to maximize the Signal to Interference plus Noise Ratio (SINR), accounting for a constant modulus constraint as well as a similarity constraint involving a known radar waveform with some desired properties (e.g., in terms of pulse compression and ambiguity). The presented sequential optimization algorithms, based on a relaxation method, yield solutions with good accuracy. Their computational complexity is linear in the number of iterations and trials in the randomized procedure and polynomial in the receive filter length. Finally, we evaluate the proposed techniques, by considering their SINR performance, beam pattern as well as pulse compression property, via numerical simulations.

Bio-sonar signal processing

An ideal sonar for biological observations in the ocean should employ very long signals for Doppler resolution, wide bandwidth for time resolution and pulse compression properties for gain in order to reduce sound pressure levels to mitigate marine mammal concerns. Signal spread in time and Doppler (leakage) must also be eliminated so that direct arrival and reverberation signals do not leak and swamp bio-signal returns when operation in a continuous transmit and receive mode. Orthogonal codes would help multi-static applications. Here two types of signals and processing are presented and analyzed; 1) M-sequences with matched filter processing and 2) Inverted binary sequence with matched- inverse processing. Ambiguity diagrams of conventional active sonar signals are compared with the two candidate signals. Then the two methods are compared by numerical simulation for propagation in shallow channels with zero Doppler returns and moving bio-scatterers. It is shown that for realistic conditions leakage from direct and zero Doppler reverberation can be eliminated not just reduced. Limits on temporal coherence times of shallow water propagations channels are discussed. These approaches improve Figure of Merit of conventional active sonar by 10 to 15 dB and displays in the time Doppler plane simplify the interpretation of clutter.

Focusing and amplification of electromagnetic waves by time reversal in an leaky reverberation chamber

Abstract In this article, time reversal is used to generate high power microwave pulses from a low power arbitrary wave generator. We use a reverberation chamber with an aperture on the front face and we take advantage of the pulse compression property of time reversal. High amplitude peaks are generated outside the chamber thanks to the long spreading time of the signals inside. We study the amplitude of this peak and the width of the focal spot with respect to the different experimental parameters. A gain of 18 dB compared to a directive antenna of the same aperture is obtained.

High resolution population density imaging of random scatterers with the matched filtered scattered field variance

The matched filter enables imaging with high spatial resolution and high signal-to-noise ratio by coherent correlation with the expected field from what is assumed to be a discrete scatterer. In many physical imaging systems, however, returns from a large number of randomized scatterers, ranging from thousands to millions of individuals, are received together and the coherent or expected field vanishes. Despite this, it is shown that cross-spectral coherence in the matched filtered variance retains a pulse compression property that enables high-resolution imaging of scatterer population density. Analytic expressions for the statistical moments of the broadband matched filtered scattered field are derived in terms of the medium's Green's function, object scatter function, and spatial distribution using a single-scatter approximation. The formulation can account for potential dispersion in the medium and target over the signal bandwidth, and can be used to compare the relative levels of the coherent and incoherent scattered intensities. The analytic model is applied to investigate population density imaging of fish distributions in the Gulf of Maine with an ultrasonic echosounder. The results are verified with numerical Monte-Carlo simulations that include multiple scattering, illustrating that the single-scatter approximation is valid even for relatively dense Atlantic herring (Clupea harengus) schools.

High‐resolution population density imaging of random scatterers through cross‐spectral coherence in matched filter variance

The matched filter enables imaging with high spatial resolution and high signal‐to‐noise ratio by coherent correlation with the expected field from what is assumed to be a discrete scatterer. In many imaging systems, however, returns from large numbers of scatterers are received together and the coherent or expected field vanishes. This is the case when imaging schools of fish, other groups of marine life, or other diffuse scatterers in sonar or ultrasound applications. Here we show that despite the absence of an expected field, cross spectral coherence in the matched filter variance retains a pulse compression property that enables high‐resolution imaging of scatterer population density. Both analytic and numerical models are developed for active imaging systems. We show the conditions for when the coherent intensity can be neglected. The model is implemented for several scenarios where single scattering dominates and also for cases where multiple scattering is important. It can applied to imaging in both free space and waveguide environments.

The analysis of signals containing multiple chirps

The analysis of signals containing multiple chirps occurs in many situations in acoustics, for example, in the bioacoustics field in analyzing the sounds of bats and dolphins. In sonar and seismic, chirp signals are used because of their pulse compression properties. Recently, the fractional Fourier transform has shown that linear chirp signals may be recognized and this has greatly facilitated the use of these signals. This paper shows a method similar to that of the fractional transform and shows how other types of chirp signals, polynomial, and other functional forms may also be analyzed. It also looks at the resolution that can be achieved when separating chirps both in rate and in time. This is of particular relevance when dealing with dispersion in the propagation of signals through different media. Examples will be presented, for the analysis of some bat signals and for some seismic signals. The analysis of signals in the time frequency domain using piecewise linear chirps will also be demonstrated, and some further examples from synthetic seismic signals will be demonstrated.