Intelligent traffic monitoring provides information support for autonomous driving, which is widely used in intelligent transportation systems (ITSs). A method for estimating vehicle moving target parameters based on millimeter-wave radars is proposed to solve the problem of low detection accuracy due to velocity ambiguity and Doppler-angle coupling in the process of traffic monitoring. First of all, a MIMO antenna array with overlapping elements is constructed by introducing them into the typical design of MIMO radar array antennas. The motion-induced phase errors are eliminated by the phase difference among the overlapping elements. Then, the position errors among them are corrected through an iterative method, and the angle of multiple targets is estimated. Finally, velocity disambiguation is performed by adopting the error-corrected phase difference among the overlapping elements. An accurate estimation of vehicle moving target angle and velocity is achieved. Through Monte Carlo simulation experiments, the angle error is 0.1° and the velocity error is 0.1m/s. The simulation results show that the method can be used to effectively solve the problems related to velocity ambiguity and Doppler-angle coupling, meanwhile the accuracy of velocity and angle estimation can be improved. An improved algorithm is tested on the vehicle datasets that are gathered in the forward direction of ordinary public scenes of a city. The experimental results further verify the feasibility of the method, which meets the real-time and accuracy requirements of ITSs on vehicle information monitoring.

In this paper, we present a novel discriminative dictionary learning (DDL) method for image classification. The local structural relationship between samples is first built by the Laplacian eigenmaps (LE), and then integrated into the basic DDL frame to suppress inter-class ambiguity in the feature space. Moreover, in order to improve the discriminative ability of the dictionary, the category label information of training samples is formulated into the objective function of dictionary learning by considering the discriminative promotion term. Thus, the data points of original samples are transformed into a new feature space, in which the points from different categories are expected to be far apart. The test results based on the real dataset indicate the effectiveness of this method.

Recently, we introduced a new automata model, so-called colored finite automata (CFAs) whose accepting states are multi-colored (i.e., not conventional black-and-white acceptance) in order to classify their input strings into two or more languages, and solved the specific complexity problems concerning color-unmixedness of nondeterministic CFA. That is, so-called UV, UP, and UE problems are shown to be NLOG-complete, P, and NP-complete, respectively. In this paper, we apply the concept of colored accepting mechanism to pushdown automata and show that the corresponding versions of the above-mentioned complexity problems are all undecidable. We also investigate the case of unambiguous pushdown automata and show that one of the problems turns out to be permanent true (the others remain undecidable).

In a 1-out-of-n oblivious signature scheme, a user provides a set of messages to a signer for signatures but he/she can only obtain a valid signature for a specific message chosen from the message set. There are two security requirements for 1-out-of-n oblivious signature. The first is ambiguity, which requires that the signer is not aware which message among the set is signed. The other one is unforgeability which requires that the user is not able to derive any other valid signature for any messages beyond the one that he/she has chosen. In this paper, we provide a generic construction of 1-out-of-n oblivious signature. Our generic construction consists of two building blocks, a commitment scheme and a standard signature scheme. Our construction is round efficient since it only asks one interaction (i.e., two rounds) between the user and signer. Meanwhile, in our construction, the ambiguity of the 1-out-of-n oblivious signature scheme is based on the hiding property of the underlying commitment, while the unforgeability is based on the binding property of the underlying commitment scheme and the unforgeability of the underlying signature scheme. Moreover, our construction can also enjoy strong unforgeability as long as the underlying building blocks have strong binding property and strong unforgeability respectively. Given the fact that commitment and digital signature are well-studied topics in cryptography and numerous concrete schemes have been proposed in the standard model, our generic construction immediately yields a bunch of instantiations in the standard model based on well-known assumptions, including not only traditional assumptions like Decision Diffie-Hellman (DDH), Decision Composite Residue (DCR), etc., but also some post-quantum assumption like Learning with Errors (LWE). As far as we know, our construction admits the first 1-out-of-n oblivious signature schemes based on the standard model.

In this letter, we discuss the ambiguity function of interleaved sequences. Furthermore, using the Guassian sum and choosing binary m-sequences as column sequences, we investigate the property of a binary sequence set given by Zhou, Tang, Gong (IEEE Trans. Inf. Theory, 54(9), 2008), which has low ambiguity property in a large region. Those sequences could be used in radar systems.

Fresh Tea Shoot Maturity Estimation (FTSME) is the basement of automatic tea picking technique, determines whether the shoot can be picked. Unfortunately, the ambiguous information among single labels and uncontrollable imaging condition lead to a low FTSME accuracy. A novel Fresh Tea Shoot Maturity Estimating method via multispectral imaging and Deep Label Distribution Learning (FTSME-DLDL) is proposed to overcome these issues. The input is 25-band images, and the output is the corresponding tea shoot maturity label distribution. We utilize the multiple VGG-16 and auto-encoding network to obtain the multispectral features, and learn the label distribution by minimizing the Kullback-Leibler divergence using deep convolutional neural networks. The experimental results show that the proposed method has a better performance on FTSME than the state-of-the-art methods.

For the blind estimation of short-code direct sequence spread spectrum (DSSS) signal pseudo-noise (PN) sequences, the eigenvalue decomposition (EVD) algorithm, the singular value decomposition (SVD) algorithm and the double-periodic projection approximation subspace tracking with deflation (DPASTd) algorithm are often used to estimate the PN sequence. However, when the asynchronous time delay is unknown, the largest eigenvalue and the second largest eigenvalue may be very close, resulting in the estimated largest eigenvector being any non-zero linear combination of the really required largest eigenvector and the really required second largest eigenvector. In other words, the estimated largest eigenvector exhibits unitary ambiguity. This degrades the performance of any algorithm estimating the PN sequence from the estimated largest eigenvector. To tackle this problem, this paper proposes a spreading sequence blind estimation algorithm based on the rotation matrix. First of all, the received signal is divided into two-information-period-length temporal vectors overlapped by one-information-period. The SVD or DPASTd algorithm can then be applied to obtain the largest eigenvector and the second largest eigenvector. The matrix composed of the largest eigenvector and the second largest eigenvector can be rotated by the rotation matrix to eliminate any unitary ambiguity. In this way, the best estimation of the PN sequence can be obtained. Simulation results show that the proposed algorithm not only solves the problem of estimating the PN sequence when the largest eigenvalue and the second largest eigenvalue are close, but also performs well at low signal-to-noise ratio (SNR) values.

The measurement accuracy of frequency difference of arrival (FDOA) is usually determinant for emitters location system using rapidly moving receivers. The classic technique of expanding the integration time of the cross ambiguity function (CAF) to achieve better performance of FDOA is likely to incur a significant computational burden especially for wideband signals. In this paper, a nonconsecutive short-time CAF's methods is proposed with expansion of root mean square (RMS) integration time, instead of the integration time, and a factor of estimation precision improvement is given which is relative to the general consecutive method. Furthermore, by analyzing the characteristic of coherent CAF and the influence of FDOA rate, an upper bound of the precision improvement factor is derived. Simulation results are provided to confirm the effectiveness of the proposed method.

Ranging is commonly used to measure the distance to a satellite, since it is one of the quickest and most effective methods of finding the position of a satellite. In general, ranging ambiguity is easily resolved using major and subsequent ambiguity-resolving tones. However, an induced unknown phase error could interfere with resolving the ranging ambiguity. This paper suggests an effective and practical method to resolve the ranging ambiguity without changing the original planned ranging tone frequencies when an unknown non-linear phase error exists. Specifically, the present study derives simple equations for finding the phase error from the physical relationship between the measured major and minor tones. Furthermore, a technique to select the optimal ambiguity integer and correct phase error is provided. A numerical analysis is performed using real measurements from a low earth orbit (LEO) satellite to show its suitability and effectiveness. It can be seen that a non-ambiguous range is acquired after compensating the unknown phase error.

The composite binary offset carrier (CBOC) modulated signal contains multi-peaks in its auto-correlation function, which brings ambiguity to the signal acquisition process of a GNSS receiver. Currently, most traditional ambiguity-removing schemes for CBOC signal acquisition approximate CBOC signal as a BOC signal, which may incur performance degradation. Based on Galileo E1 CBOC signal, this paper proposes a novel adaptive ambiguity-removing acquisition scheme which doesn't adopt the approximation used in traditional schemes. According to the energy ratio of each sub-code of CBOC signal, the proposed scheme can self-adjust its local reference code to achieve unambiguous and precise signal synchronization. Monte Carlo simulation is conducted in this paper to analyze the performance of the proposed scheme and three traditional schemes. Simulation results show that the proposed scheme has higher detection probability and less mean acquisition time than the other three schemes, which verify the superiority of the proposed scheme.

Instantaneous ambiguity resolution techniques are methods employed to achieve real-time high-accuracy positioning. The advent of the Chinese BeiDou system enables us to evaluate the performance of the combined GPS/BeiDou/QZSS dual-frequency ambiguity resolution and BeiDou three-frequency ambiguity resolution. It is known that the increasing number of satellites used can increase the reliability as well as the availability of single-epoch real-time kinematic (RTK) information. Therefore, performance improvement of single-epoch RTK by adding BeiDou satellites is strongly expected because many BeiDou satellites are operated in Asian regions. The first objective of this study is to conduct an initial assessment of the single-epoch RTK performance, as well as standalone positioning/code relative positioning using GPS/BeiDou/QZSS. The second objective of this study is to evaluate the performance of the longer-baseline single-epoch ambiguity resolution using the three-frequency observation data. Furthermore, the possibility of future single-epoch RTK service is discussed in this paper.

In digital communication systems employing binary phase-shift keying and non-data-aided carrier phase recovery, a 180 carrier phase ambiguity is inevitable. Here, we propose a simple modification to the standard regular repeat-accumulate (RA) code structure by exploiting the differential encoding inherent to the inner encoder of RA codes resulting in codes that are 180 rotationally invariant. The proposed code structure exhibit performance virtually identical to that of standard regular RA codes with zero carrier phase offset under both zero and 180 carrier phase offsets with negligible additional hardware complexity.

This paper proposes a novel MIMO system that introduces a heterogeneous stream (HTS) scheme and a blind signal detection method for mobile radio communications. The HTS scheme utilizes different modulation or coding methods for different MIMO streams, and the blind detection method requires no training sequences for signal separation, detection, and channel estimation. The HTS scheme can remove the ambiguity in identifying separated streams without unique words that are necessary in conventional MIMO blind detection. More specifically, two examples of HTS are considered: modulation type HTS (MHTS) and timing-offset type HTS (THTS). MHTS, which utilizes different modulation constellations with the same bandwidth for different streams, has been previously investigated. This paper proposes THTS which utilizes different transmission timing with the same modulation. THTS can make the blind detection more robust and effective with fractional sampling. The blind joint processing of detection and channel estimation performs adaptive blind MIMO-MLSE and is derived from an adaptive blind MLSE equalizer that employs the recursive channel estimation with the Moore-Penrose generalized inverse. Computer simulations show that the proposed system can achieve superior BER performance with Eb/N0 degradation of 1 dB in THTS and 2.5 dB in MHTS compared with the ideal maximum likelihood detection.

When a linearly polarized light is launched into a birefringent material, the output light is generally elliptically polarized. The ratio of the major and minor axes of the polarization ellipse varies depending on the angle between the polarization direction of the input light and the birefringent axis of the medium. The maximum ratio is determined only by the retardation due to the birefringence. Utilizing this phenomena, birefringence of a medium whose principal axis direction is unclear is measured with high precision by measuring the maximum extinction ratio for various input light polarization directions. Ambiguity in retardation associated with angular function solution is removed by measurement at two adjacent wavelengths. The measurement principle of the new method is confirmed by applying it to a quarter wave plate made of quartz. Birefringence of a 3 m long ribbon fiber as small as 10-7 is successfully measured.

In this paper, we are concerned with a structural ambiguity problem of tree adjoining grammars (TAGs), which is an essential problem when we try to model consensus structures of given set of ribonucleic acid (RNA) secondary structures by TAGs. RNA secondary structures can be represented as strings with structural information, and TAGs have a descriptive capability of this kind of strings, what we call structure-annotated strings. Thus, we can model RNA secondary structures by TAGs. It is sufficient to use existing alignment methods for just computing the optimal alignment between RNA secondary structures. However, when we also want to model the resulting alignment by grammars, if we adopt these existing methods, then we may fail in modeling the alignment result by grammars. Therefore, it is important to introduce a new alignment method whose alignment results can be appropriately modeled by grammars. In this paper, we will propose an alignment method based on TAG's derivations each corresponding to a given RNA secondary structure. For an RNA secondary structure, there exist a number of derivations of TAGs which correspond to the structure. From the grammatical point of view, the property of TAGs drives us to the question how we should choose a derivation from these candidates in order to obtain an optimal alignment. This is the structural ambiguity problem of TAGs, which will be mainly discussed in this paper. For dealing with this problem appropriately, we will propose an edit distance between two structure-annotated strings, and then present an algorithm which computes an optimal alignment based on the edit distance.

This paper presents an efficient and generic solution in the following scenario: There are n independent people using variety of signature schemes such as DSS, RSA, Schnorr, and so on, and a subset of them attempts to sign a document without being identified which subset they are. This is a generalized scenario of the Ring Signatures by Rivest, Shamir and Tauman, whose original scenario limits the subset to be a single person and the base signature scheme to be RSA/Rabin schemes. Our scheme allows any signature schemes based on sigma-protocols and claw-free permutations. It also offers shorter signatures and less computation compared to known generic construction. The security is argued in the random oracle model as well as previous schemes and shows that our scheme achieves reduction cost linear in the number of hash queries while it is square for previous generic constructions.

This paper addresses how to use public-keys of several different signature schemes to generate 1-out-of-n signatures. Previously known constructions are for either RSA-type keys only or DL-type keys only. We present a widely applicable method to construct a 1-out-of-n signature scheme that allows mixture use of different flavors of keys at the same time. The resulting scheme is more efficient than previous schemes even if it is used only with a single type of keys. With all DL-type keys, it yields shorter signatures than the ones of the previously known scheme based on the witness indistinguishable proofs by Cramer, et al. With all RSA-type keys, it reduces both computational and storage costs compared to that of the Ring signatures by Rivest, et al.

This paper studies the ambiguity reduction ability of a probabilistic context-free grammar. We theoretically analyze a common behavior of any probabilistic context-free grammar. Moreover, we confirm by experiments that a probabilistic context-free grammar learnt from Japanese corpus has the ambiguity reduction ability as expected by the theoretical analysis.

The paper deals with Kleenean functions defined as fuzzy logic functions with constants. Kleenean functions provide a means of handling conditions of indeterminate truth value (ambiguous states) which ordinary classical logic (binary logic) cannot cope with. This paper clarifies a necessary and sufficient condition for a function to be a Kleenean function. The condition is provided with a set of two conditions, and it will be shown that they are independent of each other.

The local moment functions for discrete Wigner trispectrum are examined in ambiguity and in time-frequency domain. A concept of multiple and multidimensional circular convolution in frequency domain is introduced into the discrete Wigner higher order time-frequency signal representation of any order. It is shown that this concept based on the 1st order spectra of the signal offers an insight into the properties of inconsistent local moment functions and their representation both in ambiguity and time-frequency domain. It allows to prove that midfrequency crossterms of a multicomponent signal can not be removed by any generalized 4th order ambiguity function which employ kernel function in the ambiguity domain. It is shown, that the concept of multiple convolution in frequency domain can lead to the crossterm-reduced discete time-frequency representations of any order