Joint Waveform Research Articles

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

We consider a hybrid active-passive radar system that employs a wireless source as a passive illuminator of opportunity (IO) and a co-channel active radar transmitter operating in the same frequency band to seek spectral efficiency. The hybrid system can take advantage of the strengths of passive radar (e.g., energy efficiency, bi-/multi-static configuration, and spatial diversity) as well as those of active radar (dedicated transmitter, flexible transmit beam steering, waveform optimized for sensing, etc.). To mitigate the mutual interference and location-induced timing uncertainty between the radar and communication signals, we propose two designs for the joint optimization of the radar waveform and receive filters. The first is a max-min (MM) criterion that optimizes a worst-case performance metric over a timing uncertainty interval, and the other a weighted-sum (WS) criterion that forms a weighted sum of the performance metric at each delay within the delay uncertainty interval. Both design criteria result in nonconvex constrained optimization problems that are solved by sequential convex programming methods. When timing uncertainty vanishes, the two designs become identical and admit a simpler solution. Numerical results are presented to demonstrate the performance of the proposed hybrid schemes in comparison with conventional active-only and passive-only radar systems.

Joint Waveform and Guidance Control Optimization for Target Rendezvous

The algorithm developed in this paper jointly selects the optimal transmitted waveform and the control input so that a radar sensor on a moving platform with linear dynamics can reach a target by minimizing a predefined cost. The cost proposed in this paper accounts for the energy of the transmitted radar signal, the energy of the platform control input, and the relative position error between the platform and the target, which is a function of the waveform design and control input. Similarly to the linear quadratic Gaussian control problem, we demonstrate that the optimal solution satisfies the separation principle between filtering and optimization and, therefore, the optimum can be found analytically. The performance of the proposed solution is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps. Results show the effectiveness of the proposed approach for optimal waveform design and optimal guidance control.

Toward Millimeter-Wave Joint Radar Communications: A Signal Processing Perspective

Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Such a joint radar communications (JRC) model has advantages of low cost, compact size, less power consumption, spectrum sharing, improved performance, and safety due to enhanced information sharing. Today, millimeter-wave (mmwave) communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several gigahertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical to the implementation of mm-wave JRC systems. Major challenges are joint waveform design and performance criteria that would optimally trade off between communications and radar functionalities. Novel multiple-input, multiple-output (MIMO) signal processing techniques are required because mm-wave JRC systems employ large antenna arrays. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. This article provides a signal processing perspective of mm-wave JRC systems with an emphasis on waveform design.

Proximal cueing to reduce elbow extension levels in suspect spin bowlers: A case study

Cricket bowlers must be able to deliver the ball with less than 15° of elbow extension or face suspension. The aim of this case study was to report the findings of a technique remediation programme on the elbow joint kinematics of an international cricket bowler. The bowler underwent a three-dimensional bowling analysis to measure his elbow joint kinematics before and after a technique remediation programme. The bowler was required to bowl six deliveries of each of his off-break, quicker and doosra variations. The remediation programme focussed on modifying the bowler’s run-up, shoulder alignment and ball/hand position at back foot impact. Elbow joint waveform data were analysed using statistical parametric mapping tests and coefficient of multiple determination. Elbow flexion–extension angles at discrete events were compared pre- and post-remediation using paired-sample t-tests. Results showed that the remediation programme was effective in reducing the amount of elbow flexion, particularly in the first 60% of the delivery cycle. Elbow extension range was significantly lower post-remediation for the off-break and quicker deliveries. It was concluded that basic short-term technique remediation can be effective in reducing elbow extension range.

FDA-OFDM for integrated navigation, sensing, and communication systems

Integrated wireless communications, radar sensing, and smart navigation is becoming increasingly necessary owing to their similar finite radio frequency (RF) electromagnetic spectrum resource [1]. By integration of various disciplines, a multitude of new and more intelligent services, such as smart city and ambient assistant living, can become available. For instance, using a joint waveform for both radar and communication applications, the occupied spectrum would be used in a more efficiently way and both applications could be operated simultaneously. Such an integrated radar and communication systems has been reported in multiple papers [2]–[9]. An early example of integrated radar and communication system is the National Aeronautics and Space Administration Space Shuttle Orbiter [10]. Another example is the intelligent transportation system [11], which allows the intelligent vehicles to autonomously sense the driving environment and cooperatively exchange the information data. Furthermore, the proposals for integrating cognitive radar and cognitive radio for efficient spectrum sharing are also suggested [12]. Many applications would possibly benefit from the availability of integrated navigation, sensing, and communications, which advantages can be summarized as follows [1]: (i) System cost is reduced and resource utilization is improved; (ii) The advantages of radar, such as high power and strong directivity, can be utilized to improve the communication quality and increase the effective sensing range; (iii) System automation level is enhanced.

MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission

Beamforming techniques are proposed for a joint multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single device acts both as a radar and a communication base station (BS) by simultaneously communicating with downlink users and detecting radar targets. Two operational options are considered, where we first split the antennas into two groups, one for radar and the other for communication. Under this deployment, the radar signal is designed to fall into the null-space of the downlink channel. The communication beamformer is optimized such that the beampattern obtained matches the radar's beampattern while satisfying the communication performance requirements. To reduce the optimizations' constraints, we consider a second operational option, where all the antennas transmit a joint waveform that is shared by both radar and communications. In this case, we formulate an appropriate probing beampattern, while guaranteeing the performance of the downlink communications. By incorporating the SINR constraints into objective functions as penalty terms, we further simplify the original beamforming designs to weighted optimizations, and solve them by efficient manifold algorithms. Numerical results show that the shared deployment outperforms the separated case significantly, and the proposed weighted optimizations achieve a similar performance to the original optimizations, despite their significantly lower computational complexity.

IEEE 802.11ad-Based Radar: An Approach to Joint Vehicular Communication-Radar System

Millimeter-wave (mmWave) radar is widely used in vehicles for applications such as adaptive cruise control and collision avoidance. In this paper, we propose an IEEE 802.11ad-based radar for long-range radar (LRR) applications at the 60 GHz unlicensed band. We exploit the preamble of a single-carrier physical layer frame, which consists of Golay complementary sequences with good correlation properties that make it suitable for radar. This system enables a joint waveform for automotive radar and a potential mmWave vehicular communication system based on the mmWave consumer wireless local area network standard, allowing hardware reuse. To formulate an integrated framework of vehicle-to-vehicle communication and LRR, we make typical assumptions for LRR applications, incorporating the full duplex radar operation. This new feature is motivated by the recent development of systems with sufficient isolation and self-interference cancellation. We develop single- and multi-frame radar receiver algorithms for target detection as well as range and velocity estimation for both single- and multi-target scenarios. Our proposed radar processing algorithms leverage channel estimation and time–frequency synchronization techniques used in a conventional IEEE 802.11ad receiver with minimal modifications. Analysis and simulations show that in a single-target scenario, a gigabits-per-second data rate is achieved simultaneously with cm-level range accuracy and cm/s-level velocity accuracy. The target vehicle is detected with a high probability (above 99.99 $\%$ ) at a low false alarm rate of 10 $^{-6}$ for an equivalent isotropically radiated power of 40 dBm up to a vehicle separation distance of about 200 m. The proposed IEEE 802.11ad-based radar meets the minimum accuracy/resolution requirement of range and velocity estimates for LRR applications.

Biomechanical characteristics of lower limb gait waveforms: Associations with body fat in children

BackgroundChildhood obesity is associated with musculoskeletal dysfunction and altered lower limb biomechanics during gait. Few previous studies have explored relationships between childhood obesity measured by body fat and lower limb joint waveform kinematics and kinetics. Research questionWhat is the association between body fat and hip, knee and ankle joint angles and moments during gait and in 7 to 11 year-old boys? MethodsFifty-five boys participated in the study. Body fat was measured by air displacement plethysmography. Hip, knee and ankle 3D waveforms of joint angles and moments were recorded during gait. Principle component analysis was used to reduce the multidimensional nature of the waveform into components representing parts of the gait cycle. Multiple linear regression analysis determined the association between the components with body fat. ResultsHigher body fat predicted greater hip flexion, knee flexion and knee internal rotation during late stance and greater ankle external rotation in late swing/early stance. Greater hip flexion and adduction moments were found in early stance with higher body fat. In mid-stance, greater knee adduction moments were associated with high body fat. Finally, at the ankle, higher body fat was predictive of greater internal rotation moments. SignificanceThe study presents novel information on relationships between body fat and kinematic and kinetic waveform analysis of paediatric gait. The findings suggest altered lower limb joint kinematics and kinetics with high body fat in young boys. The findings may help to inform research in to preventing musculoskeletal comorbidities and promoting weight management.

Adaptive Interference Removal for Uncoordinated Radar/Communication Coexistence

Most existing approaches to coexisting communication/radar systems assume that the radar and communication systems are coordinated, i.e., they share information, such as relative position, transmitted waveforms, and channel state. In this paper, we consider an uncoordinated scenario where a communication receiver is to operate in the presence of a number of radars, of which only a subset may be active, which poses the problem of estimating the active waveforms and the relevant parameters thereof, so as to cancel them prior to demodulation. Two algorithms are proposed for such a joint waveform estimation/data demodulation problem, both exploiting sparsity of a proper representation of the interference and of the vector containing the errors of the data block, so as to implement an iterative joint interference removal/data demodulation process. The former algorithm is based on classical on-grid compressed sensing, whereas the latter forces an atomic norm (AN) constraint: In both cases the radar parameters and the communication demodulation errors can be estimated by solving a convex problem. We also propose a way to improve the efficiency of the AN-based algorithm. The performance of these algorithms are demonstrated through extensive simulations, taking into account a variety of conditions concerning both the interferers and the respective channel states.

Applying joint traveltime and waveform inversion to image the Sichuan Basin, China

ABSTRACTWe apply a joint first‐arrival traveltime and early‐arrival waveform inversion method to image complex near‐surface structures in the Sichuan Basin, China. The area includes rugged topography and large near‐surface velocity variations. Due to the near‐surface effects, it is difficult to produce high‐quality reflection images of the deep subsurface. First‐arrival traveltime tomography is often applied for near‐surface imaging, but the results may not be sufficiently accurate because of ray assumptions and the limited traveltime information. Waveform inversion should allow complex structures to be resolved; however, it may fall into local minima because of cycle skipping issues and may also produce artefacts in very shallow areas that are associated with rugged topography. Therefore, we combine the advantages of the two methods and mitigate their problems by performing joint inversion of the two types of data. We demonstrate the effectiveness of the joint inversion method using synthetic and real data from Sichuan, China. In the real data example, we compare the velocity models resolved from waveform inversion alone with those resolved from the joint inversion. We calculate long‐wavelength static corrections and apply them to the data processing. The common midpoint stacking results show that the joint inversion method produces a more effective statics solution.

A New Iterative Approach in SINR Improvement of MIMO Radars by Using Combination of Orthogonal Waveforms

In this paper we consider joint waveform and filter design in multi-input multi-output (MIMO) radars in the presence of signal dependent interference to improve signal-to-interference-plus-noise ratio (SINR) of received signals. We have proposed two new iterative methods for this in which instead of direct design of waveforms, the coefficients of orthogonal waveform combinations are designed. In the first method, coefficients of combinations are calculated by solving a convex optimization problem. By extending the first method, we have proposed a method for multi-target case in presence of signal dependent interference. However, the computational complexity of the first method is high and therefore we have proposed the second method, which is more suitable for real time applications. In the second method, in each step, waveform combination coefficients and received filter coefficients are designed in closed form. Simulation results show that the proposed methods can achieve higher SINR in comparison to other methods which are used in MIMO and phased array radars.

Nonlinear inversion of tilt‐affected very long period records of explosive eruptions at Fuego volcano

AbstractMagmatic processes produce a rich variety of volcano seismic signals, ranging over several orders of magnitude in frequency and over a wide range of mechanism types. We examined signals from 400 to 10 s period associated with explosive eruptions at Fuego volcano, Guatemala, that were recorded over 19 days in 2009 on broadband stations with 30 s and 60 s corner periods. The raw data from the closest stations include tilt effects on the horizontal components but also have significant signal at periods below the instrument corners on the vertical components, where tilt effects should be negligible. We address the problems of tilt‐affected horizontal waveforms through a joint waveform inversion of translation and rotation, which allows for an investigation of the varying influence of tilt with period. Using a phase‐weighted stack of six similar events, we invert for source moment tensor using multiple bands. We use a grid search for source type and constrained inversions, which provides a quantitative measure of source mechanism reliability. The 30‐10 s band‐pass results are consistent with previous work that modeled data with a combined two crack or crack and pipe model. At the longest‐period band examined, 400‐60 s, the source mechanism is like a pipe that could represent the shallowest portion of the conduit. On the other hand, source mechanisms in some bands are unconstrained, presumably due to the combined tilt‐dominated and translation‐dominated signals, which are not coincident in space and have different time spans.

Monitoring gas leakages simulated in a near surface aquifer of the Ellerbek paleo-channel

Renewable energy resources are intermittent and need buffer storage to bridge the time-gap between production and demand peaks. The North German Basin has a very large capacity for compressed air/gas energy storage (CAES) in porous saltwater reservoirs and salt cavities. Even though these geological storage systems are constructed with high caution, accidental gas leakages occurred in the past. Stored gases migrated from deep reservoirs along permeable zones upwards into shallow potable aquifers. These CAES leakages cause changes in the electro-elastic properties, and density of the aquifers, and therefore justify investigations with the application of different geophysical techniques. A multiphase flow simulation has been performed to create a realistic virtual CAES leakage scenario into a shallow aquifer in Northern Germany. This scenario is used to demonstrate the detecting resolution capability of a combined geophysical monitoring approach, consisting of acoustic joint waveform inversion (FWI) of surface and borehole data, electrical resistivity tomography (ERT) and gravity. This combined approach of geophysical multi-techniques was able to successfully map the shape and determine the physical properties of the simulated gas phase body at a very early stage after leakage began. Techniques of FWI and ERT start to resolve CAES leakage anomalies only a few years and gravity even a few months after leakage began. Geophysical monitoring of vast areas may start by conducting time-effective aero-surveys (e.g. electromagnetic induction or gravity gradient methods) to isolate anomalous subareas of potential leakage risks. These subareas are then studied in detail using our combined high-resolution approach. In conclusion, our approach is sensitive to CAES leakages and can be used for monitoring.

Joint waveform optimization and adaptive processing for random phase radar signals

We consider waveform design for colocated multiple-input, multiple-output (MIMO) radar systems where the signal phase is subject to random phase perturbations during propagation. We formulate an iterative algorithm to obtain both waveform parameters and the space-time adaptive weights to maximize the signal-to-interference-plus-noise ratio (SINR). We ensure that the impact of the chosen waveforms on the interference signal is accounted for when modeling the second-order interference statistics. The waveform design technique is then extended to include peak-to-average power constraints. An example of a clutter and target model is provided to show how the optimal waveform design improves radar detection performance in the presence of the signal phase randomization.

To sort or not to sort: the impact of spike-sorting on neural decoding performance

Objective. Brain–computer interfaces (BCIs) are a promising technology for restoring motor ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical trials to control multi-degree-of-freedom robotic devices. Current implementations of these devices require a lengthy spike-sorting step, which is an obstacle to moving this technology from the lab to the clinic. A viable alternative is to avoid spike-sorting, treating all threshold crossings of the voltage waveform on an electrode as coming from one putative neuron. It is not known, however, how much decoding information might be lost by ignoring spike identity. Approach. We present a full analysis of the effects of spike-sorting schemes on decoding performance. Specifically, we compare how well two common decoders, the optimal linear estimator and the Kalman filter, reconstruct the arm movements of non-human primates performing reaching tasks, when receiving input from various sorting schemes. The schemes we tested included: using threshold crossings without spike-sorting; expert-sorting discarding the noise; expert-sorting, including the noise as if it were another neuron; and automatic spike-sorting using waveform features. We also decoded from a joint statistical model for the waveforms and tuning curves, which does not involve an explicit spike-sorting step. Main results. Discarding the threshold crossings that cannot be assigned to neurons degrades decoding: no spikes should be discarded. Decoding based on spike-sorted units outperforms decoding based on electrodes voltage crossings: spike-sorting is useful. The four waveform based spike-sorting methods tested here yield similar decoding efficiencies: a fast and simple method is competitive. Decoding using the joint waveform and tuning model shows promise but is not consistently superior. Significance. Our results indicate that simple automated spike-sorting performs as well as the more computationally or manually intensive methods used here. Even basic spike-sorting adds value to the low-threshold waveform-crossing methods often employed in BCI decoding.

A Multidisciplinary Study of the DPRK Nuclear Tests

The Democratic People Republic of Korea announced two underground nuclear tests carried out in their territory respectively on October 9th, 2006 and May 25th, 2009. The scarce information on the precise location and the size of those explosions has stimulated various kinds of studies, mostly based on seismological observations, by several national agencies concerned with the Nuclear Test Ban Treaty verification. We analysed the available seismological data collected through a global high-quality network for the two tests. After picking up the arrival times at the various stations, a standard location program has been applied to the observed data. If we use all the available data for each single event, due to the different magnitude and different number of available stations, the locations appear quite different. On the contrary, if we use only the common stations, they happen to be only few km apart from each other and within their respective error ellipses. A more accurate relative location has been carried out by the application of algorithms such as double difference joint hypocenter determination (DDJHD) and waveform alignment. The epicentral distance between the two events obtained by these methods is 2 km, with the 2006 event shifted to the ESE with respect to that of 2009. We then used a dataset of VHR TerraSAR-X satellite images to detect possible surface effects of the underground tests. This is the first ever case where these highly performing SAR data have been used to such aim. We applied InSAR processing technique to fully exploit the capabilities of SAR data to measure very short displacements over large areas. Two interferograms have been computed, one co-event and one post-event, to remove possible residual topographic signals. A clear displacement pattern has been highlighted over a mountainous area within the investigated region, measuring a maximum displacement of about 45 mm overall the relief. Hypothesizing that the 2009 nuclear test had been carried out close to the area where the displacement has been observed through the DInSAR technique, its relation with the epicenter location obtained through seismological processing has been discussed as a possible alternative hypothesis with respect to the preferred solutions reported by the nuclear explosion database (NEDB). The distance of about 10 km between the two places can be considered acceptable in light of the possible systematic location shifts commonly observed in the seismological practice over a global scale. The difference between the m b magnitudes of the two tests could reflect differences in geological conditions of the two test sites, even if the yield of the two explosions had been the same.

Waveform joint inversion of seismograms and electrograms for moment tensor characterization of fracking events

Electromagnetic signals have been observed in association with fracking experiments in the laboratory, and in the field. We have developed a seismoelectric forward modeling approach to produce synthetic seismograms and electrograms generated by fracking events using the finite-element method with perfect matched-layer boundary conditions. The poroelastodynamic equations are solved in the frequency domain using a formulation based on the solid phase displacement and the pore pressure. These results are used to compute the electrical field disturbances of electrokinetic nature. Three types of electrical signals are generated: Type I disturbance is associated with the seismic source itself, Type II disturbance corresponds to seismoelectric conversions, and Type III corresponds to coseismic signals. This model is applied to simulate the seismic and electrical signals corresponding to the occurrence of a fracking event in a two-layers system. We perform a stochastic joint inversion of the seismograms and electrograms using the adaptive Metropolis algorithm (AMA) to obtain the posterior probability density functions of the parameters characterizing the seismic source assuming that the velocity model is perfectly known. The joint waveform inversion is performed on synthetic noise-free data and the AMA algorithm is successful in retrieving the true values of the unknown parameters. The proposed approach is then tested on the same synthetic data after being contaminated with 15% random noise with respect to the maximum amplitude of the signals. The model parameters are better determined for the joint inversion of seismic and electrical data by comparison with the inversion of the seismic time-series alone. We also propose a deterministic tomographic algorithm that is successful in locating the in situ source current density distribution for Types I and II anomalies from the electrical data alone.

Reducing the Waveform Cross Correlation of MIMO Radar With Space–Time Coding

Multiple-input-multiple-output (MIMO) radar is attractive for target detection, parameter identification, and target classification due to diversity of waveform and perspective. However, the mutual interference among the waveforms may lead to performance degradation in resolving spatially close returns. In this paper, we consider the use of space-time coding (STC) to mitigate the waveform cross-correlation effects in MIMO radar. First, it turns out that a joint waveform optimization problem can be decoupled into a set of individual waveform design problems. Second, a number of monostatic waveforms can be directly used in a MIMO radar system, which offers flexibility in waveform selection. We provide conditions for the elimination of waveform cross correlation, and discuss four kinds of space time codes. In addition, we also extend the model to partial waveform cross-correlation removal based on waveform set division. Numerical results demonstrate the effectiveness of STC in MIMO radar for waveform decorrelation.