128 results about "Nested arrays" patented technology

The present invention describes a novel nucleic acid sequencing reagent which consists of a capture moiety, a spacer region and a sequence specific hybridizing region of 4-8 bases. The nucleic acid sequencing reagent of the present invention can also contain an attachment moiety. The nucleic acid sequencing reagent can be arranged into a nested array. This array configuration can then be used to sequence a given template without prior knowledge (de novo) of the wild type or expected sequence in conjunction with primer extension in the presence of a labeled chain terminating nucleotide.

The invention discloses a two-dimensional direction of arrival estimation method for a nested array based L-shaped antenna array, and belongs to the field of array signal processing. The implementation method includes the following steps: constructing a nested array based L-shaped antenna array, calculating a cross-covariance matrix by using signals received by different sub arrays of the constructed L-shaped nested array; correcting the obtained cross-covariance matrix, performing vectorization on the corrected cross-covariance matrix to generate a virtual array, constructing a plurality of equivalent covariance matrices by using the virtual array, calculating the signal azimuth angle Theta and the pitch angle Phi by using the rotation invariance between different equivalent covariance matrices, and achieving multi-target and high-precision two-dimensional direction of arrival estimation with few snapshots at a low signal-to-noise ratio. The technical problem to be solved by the invention is to realize multi-target and high-precision two-dimensional direction of arrival estimation by using fewer array elements at a low signal-to-noise ratio and with few snapshots, and to solve related engineering technical problems by using two-dimensional direction of arrival estimation results.

A light having a plurality of LEDs and a switching substrate is disclosed. The switching substrate is coupled to LEDs and includes a plurality of switches that provide a plurality of configurations for the LEDs. Each configuration is characterized by a two-dimensional array of LEDs having a minimum bias potential and a maximum bias potential, the LED array generating light when a bias potential is provided between the power terminals that is greater than the minimum bias potential, at least two configurations being operable to provide light at bias potential within this range. The switching substrate is sub-dividable into a plurality of identical multi-LED light sources by dividing the switching substrate along predetermined lines. The array of LEDs can be organized as a nested array of LEDs. The switches can be implemented as passive switches that are set by removing portions of conductors or bridging gaps in conductors.

The invention provides a DOA (direction of arrival) estimation method of a nested array based on a K-R subspace and relates to a DOA estimation method. The invention aims to solve the problems that anexisting estimation method has a large error and an antenna array only can estimate arrival waves whose DOA number is smaller than that of array elements. The method comprises the steps of (1) establishing a nested array model according to an equally spaced linear array signal model, (2) carrying out sparsity processing on the nested array model established in step (1) according to the K-R product transformation principle and obtaining a sparse matrix Phi, and (3) carrying out optimized reconstruction on the sparse matrix Phi obtained in step (2) and obtaining a DOA estimation value. According to the method, the number of more incident wave sources with the breaking of Rayleigh limitation can be estimated, when a signal to noise ratio is 20dB, a root mean square error decreases from 0.15to 0.06952, and when the number of snapshots is 500, the root mean square error decreases from 0.4031 to 0.1949. The method is used in the field of smart antennas and DOA estimation.

The invention discloses a method for estimating the direction of arrival of MIMO radar based on a nested array, which mainly solves a problem that the early radar is low in resolution for the direction of arrival and small in number of recognized signal sources. Implementation of the method comprises the steps of 1) building a nested array based MIMO radar model, and acquiring a target return signal; 2) performing snapshot sampling, matched filtering and vectorization on the target return signal in sequence, and acquiring vectorized receiving data y; 3) estimating a covariance matrix Ryy of the receiving data y, and performing vectorization on the covariance matrix Ryy to acquire an observation vector z; 4) removing repeated elements of the observation vector z to acquire virtual differential array receiving data z1; 5) dividing the virtual differential array receiving data z1 into N1 pieces of subarray receiving data, and acquiring a rank-recovery receiving data covariance matrix Rss; 6) performing eigenvalue decomposition on the rank-recovery receiving data covariance matrix Rss to acquire a noise subspace EN; and 7) acquiring the direction of arrival according to a spectral function formed by the noise subspace EN. The method disclosed by the invention improves the degree of freedom and the resolution of an MIMO radar system, and can be applied to radar target orientation detection.

The invention discloses a DOA (Direction of Arrival) estimation method based on a DFT (Discrete Fourier Transform) under a nested array, which belongs to the field of array signal processing. First, a receiving data covariance matrix is vectorized to get receiving data with the number of array elements expanded. Then, the initial DOA is estimated through a DFT method. Finally, the precise DOA is estimated by searching for the optimal phase shift in a very small area. The method of the invention has better DOA estimation performance, a complete degree of freedom and lower complexity.

The invention discloses a compressed sensing DOA estimation method based on unknown mutual coupling information in a nested array. The method includes the steps of calculating an autocorrelation matrix of received signals of a nested array; performing vectorization processing on the obtained autocorrelation matrix; constructing an optimization problem model based on the obtained vectorization result; evenly dividing the space and constructing a complete dictionary set; substituting the complete dictionary set into the optimization problem model and solving to obtain a DOA estimation blocking result; and calculating a DOA estimation result based on the DOA estimation blocking result. The method of the invention is used for DOA estimation of the nested array in the presence of a mutual coupling effect, and can effectively solve the problem that the estimation performance is seriously degraded due to the mismatch of the DOA estimation model. The method of the invention does not need the mutual coupling information and has the advantages of high degree of freedom and excellent resolution performance, and is capable of processing more incident signals than the number of physical elements.

The invention discloses a nested array direction-of-arrival angle estimation method based on fourth-order cumulants, and mainly aims to solve the problem that the utilization rate of array elements is low and only a small number of signals are identified in the prior art. The method is implemented by the steps as follows: (1) building a one-layer nested array and a two-layer nested array; (2) acquiring the output signal of the one-layer nested array and the output signal of the two-layer nested array; (3) calculating all fourth-order cumulants according to the output signal of the one-layer nested array and the output signal of the two-layer nested array; (4) constructing a fourth-order cumulant matrix according to all the fourth-order cumulants; (5) calculating the noise subspace of the fourth-order cumulant matrix; (6) calculating the space spectrum according to the noise subspace of the fourth-order cumulant matrix and an array manifold matrix; and (7) drawing an amplitude spectrogram according to the space spectrum to get the direction-of-arrival angle. The number of signal sources identified by an array is increased greatly under a limited number of array elements. The method is suitable for target reconnaissance and passive location.

The invention discloses a nested array direction-of-arrival estimation method based on off-grid sparse Bayesian learning. The method comprises: step one, matching filtering is carried out on a narrowband Gaussian signal received by a nested array to obtain a data vector x(t) including DOA information at a t time; step two, with the x(t), a received data covariance matrix R^x under a T snapshot number is calculated and vectorization is carried out on the R^x to obtain a one-dimensional data vector Y^; step three, K^ grid points theta^={theta^i}<K^>i=1 are divided uniformly in a range [-pai / 2,pai / 2], a counting variable I of the number of times for iteration is set to be 1, a variance vector delta and an e angle offset vector beta are initialized, and a measuring matrix phi (theta^, beta) isconstructed; step four, a variance vector theta and an angle deviation value beta in a (K^+1) dimension are updated by using an EM criterion; step five, the grid theta^ is updated by using the beta value obtained at the step four; step six, whether the counting variable I of the number of times for iteration reaches an upper limit L or the delta converges is determined; if not, the counting variable I of the number of times for iteration conforms to a formula: 1=1+1, wherein the beta is equal to 0; updating is carried out on the phi (theta^, beta) by using the updated grid theta ^, and the step four is performed; and step seven, spectral peak searching is carried out on the variance vector delta to obtain angles corresponding to K maximum points, so that a final estimation value of the target angle is obtained.

The invention provides a DOA estimation method under array element failure based on a matrix filled nested array. The method comprises that a reception signal covariance matrix of a virtual optimization array is calculated according to a reception signal x(t) of the nested array, the reception signal covariance matrix of the virtual optimization array is expanded into a covariance matrix of a uniform array, and a convex optimization problem in complementing zero elements in the covariance matrix of the uniform array is established, and on the premise that the non-zero elements in the covariance matrix of the uniform array are not changed, the sum of singular values of the covariance matrix of the uniform array is minimized; a fixed point prolongation algorithm in matrix filling is used tosolve the convex optimization problem to obtain an optimal value RV; and characteristic decomposition is carried out on the optimal value to obtain a noise subspace, a MUSIC score is constructed, andDOA estimation is realized by spectrum peak searching. DOA estimation is carried out by using all virtual element arrays in the sparse array, advantages of the nested array itself are reserved, and the matrix filling algorithm is used to fill more element arrays to carry out DOA estimation.

The invention discloses a direction-of-arrival (DOA) angle estimation method based on a dual-layer nested array and mainly aims at solving the problems of heavy computation, low quantity of identified information sources and great estimation error in the prior art. The DOA angle estimation method comprises the following implementation steps: firstly, respectively constructing a first-layer nested array and a second-layer nested array; secondly, acquiring an output signal of the first-layer nested array and an output signal of the second-layer nested array; thirdly, calculating all fourth-order cumulants according to the output signal of the first-layer nested array and the output signal of the second-layer nested array to form a fourth-order cumulant vector; fourthly, constructing an over-complete base according to the fourth-order cumulant vector, and defining an airspace sparse vector; fifthly, converting detection of an airspace DOA angle estimation into solving of a sparse constraint equation; sixthly, obtaining a most sparse solution of the airspace sparse vector by using a convex optimization method; seventhly, drawing an amplitude spectrum according to the most sparse solution to obtain the DOA angle. According to the DOA angle estimation method disclosed by the invention, the quantity of information sources which can be identified is greatly increased under the condition of limited array element quantity; the DOA angle estimation method can be used for target reconnaissance and passive location.

The invention discloses a non-uniform array design and direction of arrival (DOA) estimation method and mainly aims at solving the problems that arrangement is inflexible and computation complexity isrelatively high in the prior art. A realization process of the method comprises the following steps: according to maximum freedom degree of a nested array, determining head and tail position coefficients of a non-uniform array; calculating position coefficients of all the virtual array element positions meeting the non-uniform array and contained in a differential synthetic matrix; according to the position coefficients, finally obtaining positions of array elements of the non-uniform array; according to received data, calculating a data covariance matrix and vectorizing, so that received data r of a virtual differential synthetic array is obtained; performing redundancy elimination on the r and sorting to obtain received data of a virtual array, and then obtaining a non-singular matrix vof the virtual array; constructing a linear operator, and obtaining a signal subspace by estimating the linear operator; and constructing a selection matrix to obtain a rotation matrix, and finally estimating a direction of arrival by virtue of the rotation matrix. The method disclosed by the invention has the advantages that array configuration is flexible, characteristic decomposition does notneed to be performed on the data covariance matrix and spectral peak search does not need to be performed on the whole airspace angle under the same conditions.

The invention discloses a target direction-finding method based on an acoustic vector two-dimensional nested array, and is used for direction and pitching measurement of an underwater target. The method includes building a new acoustic vector two-dimensional nested array which is formed by two two-dimensional acoustic vector subarrays nested in geometric position, array elements of the subarray 1 are distributed in sparse grids, array elements of the subarray 2 are distributed in dense grids, two grids can be selected arbitrarily, that a matrix that associate the grids is an integer matrix is required only, the integer matrix can also be selected freely, then an autocorrelation matrix of signals output by the array are utilized to build a difference synthesis acoustic vector two-dimensional array, and finally a three-dimensional smooth DOA algorithm is utilized to obtain second-order statistics of received signals of the difference synthesis acoustic vector array.

The invention discloses a noncircular signal direction-of-arrival angle estimation method based on a nested array and mainly solves the problems of low utilization rate of array elements, small identified source number and low non-circular signal characteristic utilization rate in the prior art. The method is characterized by 1) obtaining an output signal of the nested array, calculating a covariance matrix and an elliptic covariance matrix according to the signal, constructing an equivalent covariance vector and an equivalent elliptic covariance vector and calculating dimensions of all elements in the two vectors; 2) calculating a virtual array covariance vector and a virtual array elliptic covariance vector, constructing a direction-of-arrival angle selection matrix and calculating a noise subspace thereof; 3) obtaining a first noise matrix and a second noise matrix according to the noise subspace, and constructing a polynomial equation according to the two noise matrixes; and 4) calculating the root of the polynomial equation to obtain a target direction-of-arrival angle value. The method improves the array- recognizable source number under a noncircular signal environment, and can be used for target reconnaissance and passive location.

A method and apparatus provide the ability to generate and use a database representing all solutions (legal combinations) satisfying all constraints of configuration problems on finite domains and / or intervals. The configuration space with all legal combinations is stored in a compact way in terms of nested arrays, where each legal Cartesian subspace has a unique index. Thus, the complete configuration space (which can be extended with object functions for optimization) is easily addressable by parallel indexing techniques and the database is therefore suitable for run-time applications (e.g. configuration on the Internet), which must be performed in real time.< / PTEXT>

The invention discloses a direction-of-arrival estimation method for supernested arrays based on sparse reconstruction and relates to the field of array signal processing. The method comprises following steps: 1. a far-field incoherent signal is incident on a constructed supernested array structure to obtain an array receive signal; 2. vectorization is performed on covariance matrix of array received signals to obtain received signals of a virtual sensor; 3. the received signal of the virtual sensor is sparse to obtain the optimization function, and then the optimization function is solved toobtain the estimation value; 4. the spatial power spectrum is constructed according to the estimated value and the divided grid points, and the azimuth angle of the signal is estimated by searching. The invention solves the problem that the DOA estimation method of the existing nested array needs to divide the continuous sensors into mutually overlapping sub-arrays to reduce the degree of freedomdue to adopting a spatial smoothing algorithm; the effect of using virtual sensors between arrays to increase the degree of freedom of the array, using sparse reconstruction algorithm to maximize thenumber of estimated sources and reduce the error is achieved.

This invention discloses an interactive sequential system to input letters of the English alphabet and of many world languages, numbers, punctuation marks and many other symbols on keypads with few buttons. The invention includes a device for receiving input characters from a user, having a keypad with a plurality of keys arranged in rows and columns forming a keypad array; a display screen showing a plurality of character sets arranged in rows and columns forming a character set onscreen array wherein each element in the character set array is mapped to each element in the keypad array; and a processor for receiving a selection of one of the plurality of keys on the keypad to designate a character set by its corresponding location coordinate as mapped on the keypad array. Sequential key selection drills down through nested arrays.

The invention discloses a MIMO radar anti-interference method based on a nested array, aiming to solve the problems of low resolution and low interference suppression capability of a conventional MIMO radar. The method includes 1) acquiring the target return signal; 2) performing snapshot sampling, matching filtering and vectorization on the target return signal successively to obtain vectorized receiving data y; 3) estimating the covariance matrix of y and performing vectorization to obtain an observation vector z; 4) removing the repetitive elements of z, and obtaining the virtual differential array receiving data z1; 5) dividing z1 into N1 subarray receiving data to obtain the received data covariance matrix Rss of rank recovery; 6) obtaining the beamformer weight vector W based on the Rss; and 7) beamforming according to W and enhancing the desired target information and suppressing the interference. The method can effectively improve the resolution of the MIMO radar and suppress the performance of the interference suppression, and can be used to suppress the interference.

The invention provides a hybrid field signal source positioning method based on a symmetrical nested array. The hybrid field signal source positioning method comprises the following steps that an antenna array is set, wherein the antenna array is the symmetrical nested array; a far-field signal DOA is estimated to obtain an estimation value of the far-field signal DOA; the near field component isseparated from the far field component; a fourth-order cumulant virtual difference array of a near-field signal is calculated; an estimation value of the near-field signal DOA is obtained by using spectral peak search; and according to the near-field signal DOA estimation value, the near-field signal distance is estimated to obtain a near-field signal distance estimation value. The hybrid field signal source positioning method uses mixed-order statistics, and compared with a second-order statistic algorithm, the hybrid field signal source positioning method solves the problems of Gaussian noise interference and reduction of degree of freedom by half; the symmetric nested array and the fourth-order cumulant virtual differential array are used for improving the estimation accuracy of far-field DOA, near-field DOA and a near-field distance; oblique projection technology is utilized to separate the far-field and near-field components, and thus, it is not necessary to distinguish the far-field signal from the near-field signal according to distance parameters; and therefore, the number of search is reduced, and the computational complexity of the algorithm is further reduced.

The invention provides a low complexity DOA and polarization joint estimation method under an electromagnetic vector nested L array. An electromagnetic vector sensor array and the nested L array are combined. Through introducing a spatial smoothing technology, smoothing processing is performed on a continuous virtual area array obtained after nested L array vectorization so as to obtain a virtualreceiving signal covariance matrix possessing a full rank characteristic. After a characteristic value is decomposed, a subspace class algorithm PM algorithm is used to realize signal DOA and polarization Information joint estimation. The electromagnetic vector sensor array can obtain the arrival angle information of the signal and can obtain the polarization information of the signal. The methodhas an important application value in the array signal processing field. In the method of the invention, space spectrum search is not needed, algorithm complexity is low, an obtained DOA estimation angle can realize automatic matching, the application of the nested array provides great array aperture support, and the high degree of freedom of a space and better parameter estimation performance arepossessed.

The invention discloses a method for estimating the DOA (direction of arrival) of a non-circular signal based on polynomial solving, and mainly solves problems that the array elements are low in utilization rate and the signal recognition number is small in the prior art. The method comprises the implementation steps: 1), obtaining an output signal of a nested array, calculating a covariance matrix and an elliptical covariance matrix according to the signal, constructing an equivalent covariance vector and an equivalent elliptical covariance vector, and calculating the dimensions of all elements in the two vectors; 2), calculating a virtual array covariance vector and a virtual array elliptical covariance vector, constructing two DOA selection matrixes, and calculating the noise subspaces; 3), obtaining a first noise matrix, a second noise matrix, a third noise matrix and a fourth noise matrix through the noise subspaces, and constructing a polynomial equation according to the two noise matrixes; 4), calculating the roots of the polynomial equation, and obtaining a target DOA value. According to the invention, the method greatly increases the number of array recognizable signal sources under the non-circular signal environment, and can be used for target detection and passive positioning.

The invention provides a self-adaptive beam forming algorithm based on nested array and covariance matrix reconstruction. The algorithm comprises the steps of S1, calculating a sample covariance matrix of a received signal; S2, uniformly dividing the whole space angle into N angle grids, and calculating a Capon power spectrum of the received signal at each angle of the angle grids; S3, carrying out spectral peak search on the Capon power spectrum to obtain direction-of-arrival estimation and power estimation of each signal source; S4, reconstructing an interference and noise covariance matrixof the received signal; S5, carrying out vectorization on the reconstructed interference and noise covariance matrix, and carrying out redundancy elimination and vector rearrangement to obtain a received data vector of a differential joint array; S6, obtaining a new sample space smoothing matrix by utilizing a spatial smoothing method; and S7, obtaining a beam forming weighted vector through the new sample space smoothing matrix and direction-of-arrival estimation of a desired signal. According to the method, the convergence speed of the sample space smoothing matrix is increased through the covariance matrix reconstruction, so that the better performance can be achieved by only requiring fewer snapshots.

The invention discloses a wave arrival direction estimation method based on an L-shaped electromagnetic vector sensor array, which mainly solves the problem that the mutual coupling is large and the parameter estimation precision is not consistent in a two-dimensional wave arrival direction estimation method of an existing nested array, and the realization steps are as follows: (1) constructing anL-shaped electromagnetic vector sensor array; (2) establishing a received data model of a target signal; (3) calculating the signal subspace matrix of the array; (4) calculating the cosine estimationvalue of the L-shaped array on the target signal; (5) calculating a fuzzy direction cosine estimation value of a single split electromagnetic vector sensor for a target signal; (6) calculating the cosine estimation value of the target signal direction after de-blurring; (7) obtaining the two-dimensional wave arrival direction of the target. According to the invention, the two-dimensional wave arrival direction estimation of the L-shaped electromagnetic vector sensor array is realized, and the method can be used for target positioning in radar and communication.

The invention provides a two-dimensional DOA estimation method based on a parallel nested array. The method comprises the steps of calculating autocorrelation matrix of a first subarray virtual optimized array receiving signal and autocorrelation matrix of a second subarray virtual optimized array receiving signal; calculating cross-correlation matrix of the first subarray virtual optimized arrayreceiving signal and the second subarray virtual optimized array receiving signal and cross-correlation matrix of a second subarray virtual optimized array and a first subarray virtual optimized array; calculating the autocorrelation matrix of the parallel nested array virtual optimized array receiving signal; calculating an estimated value of an incident signal cos alpha; calculating an estimatedvalue of cos beta; calculating an estimated value of an azimuth angle of the Kth signal and the estimated value of a pitch angle. The method uses all of the virtual array elements of a sparse array for estimation, and breaks the limit that the number of estimable signals cannot exceed the number of subarrays.

The invention discloses a DOA estimation method based on an enhanced nested array. The DOA estimation method comprises the following steps: constructing the enhanced nested array by utilizing two uniform linear arrays with different array element distances and an independent sensor; spatial sampling is carried out on the target radiation source, and vectorization processing is carried out on a covariance matrix of an antenna array receiving signal; calculating a differential common matrix of the enhanced nested array; meshing the observation airspace, and constructing an over-complete basis matrix; and converting a DOA estimation problem of the target radiation source into a problem of solving an l1 norm minimization constraint equation based on a compressed sensing method, and realizing DOA estimation of the target radiation source through spectral peak search. Based on an enhanced nested array and a compressed sensing theory, a DOA estimation problem is converted into a norm minimization constraint equation solving problem, high-precision DOA estimation can be realized under non-ideal conditions such as a low signal-to-noise ratio and a small snapshot number, and the number of estimated signal sources is greater than the number of array elements.

The invention discloses a 2q-order nested array DOA estimation method based on a multi-frequency high-order cumulant, and relates to the technical field of radar signal and information processing. Forthe problem that virtual array elements cannot be fully utilized due to the occurrence of voids in the prior art, the voids in an original high-order virtual array are filled with the virtual array elements generated by multi-frequency signals to form a continuous uniform linear array with higher degree of freedom, so that the DOA estimation performance is improved.

The invention provides a MUSIC solution-based noncircular signal direction-of-arrival angle estimation method which is used for solving the prior-art technical problem that the noncircular signal direction-of-arrival angle estimation precision is low. The method is implemented in the following steps: 1) building a nested array c; 2) acquiring an output signal Y(t) of the nested array c; 3) calculating a virtual uniform array covariance vector and an elliptic covariance vector of the nested array c; 4) building an extending covariance matrix G; 5) calculating noise subspace Un of the extendingcovariance matrix G; 6) building an array flow pattern matrix Q(theta) of a target direction-of-arrival angle theta; 7) calculating a spatial spectrum P(theta) of the target direction-of-arrival angletheta based on a MUSIC solution method; 8) drawing an amplitude spectrogram of the target direction-of-arrival angle theta and the spatial spectrum P(theta) thereof. The MUSIC solution-based noncircular signal direction-of-arrival angle estimation method can be applied to passive location on airplane and ship moving objects.

The present invention provides a nested array direction-of-arrival angle estimation method based on variational Bayesian inference. A three-layer prior distribution model is employed and variational inference is employed to find approximate distribution of posterior probability distribution to obtain an incident signal direction-of-arrival angle. A nested array formation structure is employed to perform direction-of-arrival angle estimation so as to overcome defects that a distinguishable target number is lower than an array element number when an uniform linear array is employed and improve the distinguishable target number of the array element number in the same condition, based on the sparse reconstruction theory, the posterior probability distribution of the sparse vectors to be estimated tends to be more gentle and better meet the signal sparse features, the direct solution of the posterior probability can be avoided, and therefore, the nested array direction-of-arrival angle estimation method is specially suitable for conditions with complex posterior probability and difficult solution and can reduce the operation complexity.

The invention belongs to the field of radar signal processing, and discloses a sum-difference tracking angle measurement method based on a Nested array. The method comprises the steps: obtaining the echo data of the Nested array, carrying out the vectorization of a covariance matrix of the echo data, and forming single-snapshot receiving data; removing the redundancy of the single-snapshot receiving data, and obtaining the single-snapshot receiving data of a virtual array; carrying out the reconstruction of data; enabling the reconstruction data to serve as the covariance matrix of the echo data of the virtual array when the data contains interference data, and calculating a sum wave beam weight value and a different wave beam weight value after interference resistance; carrying out the data interpolation of the echo data of the Nested array, and forming the echo data of the virtual array; obtaining a sum wave beam and a difference wave beam after interference resistance, and carrying out the sum-different tracking angle measurement; enabling the reconstruction data to serve as the multi-snapshot receiving data of the virtual array when the interference data is not contained, obtaining the sum wave beam and the difference wave beam, and carrying out the sum-different tracking angle measurement according to the sum wave form and the difference wave beam, thereby achieving the accurate sum-difference tracking.