1021results about How to "Improve estimation performance" patented technology

The invention provides a targeting system used to direct a measuring system to a targeted sample site or volume. The targeting system increases analyte estimation performance by increasing precision and accuracy of sampling and / or by targeting an analyte rich tissue volume.

The invention discloses a particle filtering method based on a Gaussian mixture model and variational Bayes, comprising the following steps: (1) modeling observation noise using a Gaussian mixture model, and initializing the initial state; (2) randomly generating N initial particles based on the probability density function of the initial state; (3) initializing the super parameters of the unknown parameters in the Gaussian mixture model of observation noise; (4) generating sampling particles from a chosen importance reference function; (5) updating measurement, and calculating the particle weights according to the latest observation value and a particle weight iteration formula; (7) using a variational Bayesian method to get the distribution of the unknown parameters in the Gaussian mixture model by means of loop iteration; and (7) normalizing the particle weights, and re-sampling a particle set in view of particle degradation. Through the scheme, the filtering precision and the target state estimation performance are improved effectively.

The invention relates to a direction-of-arrival estimation method on the basis of a uniform circular array, in particular to a direction-of-arrival estimation method for independent signals and coherent signals on the basis of the uniform circular array. The direction-of-arrival estimation method on the basis of the uniform circular array includes: preprocessing estimation parameters of direction-of-arrival; removing noise of pattern space; increasing aperture of the array and performing direction-of-arrival estimation to independent signals; and eliminating independent signals and performing direction-of-arrival estimation to coherent signals. The direction-of-arrival estimation method has higher estimation precision, the aperture of the array can be utilized more sufficiently, the loss of the aperture of the array due to array transformation of a virtual array is recovered, estimation performance can be improved further, calculation is simple and calculation quantity is low.

The invention discloses a frequency offset and phase estimation method based on differential phase in TD-SCDMA communication system receiving synchronization; the invention uses fractional step estimation strategy of two periods of initial frequency offset estimation and precise frequency offset and phase estimation, combines and uses two groups of pilot frequency identifier sequences in present adjacent two sub-frames having related frequency offset, implements TD-SCDMA communication system frequency offset and phase estimation through differential phase calculation. The method has precise frequency offset and phase estimation under middle and high signal-to-noise ratio; fluctuation range of estimated value is less.

The invention discloses a multiple input multiple output (MIMO) radar array position error self-correcting method based on a genetic algorithm, belonging to an MIMO radar array position error self-correcting method. The method comprises the following steps of: carrying out one-dimensional spectral peak search according to an ideal array element position by utilizing a MUSIC method to obtain the initial value theta k of direction of arrival (DOA); generating an initial group, carrying out individual fitness evaluation according to f(G), and finding out f max; carrying out genetic evolution operations of selection, crossing, heteromorphosis and the like to generate a new generation of search group, and carrying out fitness evaluation to reduce a deviation factor sigma; revising the theta k according to the optimal individual in the population; and carrying out genetic iteration until a greatest iteration number is set. By using the method, online estimation and correction of array position error can be finished while the DOA estimation is carried out, thereby the robustness of estimation of system parameters is improved.

The present invention relates to a method and an apparatus for adjusting an average interval of channel estimation dynamically based on Doppler-shift. The method comprises the steps of estimating Doppler-shift by using level cross rate (LCR) according to differently moving speeds of mobile terminals, determining the optimal average interval of channel estimation based on the relationship between the existing Doppler-shift and the optimal average interval of channel estimation, dynamically adjusting the average interval of channel estimation according to the determined the optimal average interval of channel estimation to make the coherent receiver obtain the optimal estimation performance at different moving speeds. The apparatus of the present invention comprises a channel estimation module, a valid / strongest finger selection module, a RAKE demodulation and combining module, a RAKE output decision module, an LCR detection and Doppler-shift estimation module, a Gaussian noise power estimation module, a strongest path signal power estimation module, and an optimal average interval calculation module.

A method and apparatus for allocating pilot carriers adaptively in an OFDMA communication system are disclosed. To improve phase error estimation performance and optimize the number of pilot carriers allocated to each sub-channel, an OFDMA transmitter changes the number of pilot carriers for a sub-channel according to the status of the sub-channel. Consequently, less pilot carriers are allocated to a sub-channel in a good state, reducing power consumption and more pilot carriers are allocated to a sub-channel in a bad state, improving channel estimation performance despite increased power consumption.

The invention discloses a power lithium battery model parameter identifying and dump energy estimating method. The method includes the steps of firstly, establishing a state space equation of a two-order impedance-capacitance model of a lithium battery; secondly, establishing a regression model of the relation of an end voltage and open circuit voltage and a current; thirdly, conducting parameteridentifying based on an iterative learning recursive least-squares method on the regression model; fourthly, conducting identifying based on the iterative learning recursive least-squares method on experimental data meeting the discharge current conditions in the parameter identifying process in the third step to obtain prediction errors, and conducting converging through the prediction errors toobtain a nonlinear function in parameters of the state space equation and a parameter set; fifthly, verifying the battery model precision formed by the nonlinear function and the parameter set obtained in the fourth step; sixthly, collecting current and voltage data, and estimating the dump energy through expanded Kalman filtering. The model parameter identifying precision is high, the dump energyestimation value error is small, and good application prospects are achieved.

The invention discloses a no-grid co-prime array DOA (direction of arrival) estimation method based on virtual array interpolation, and mainly solves a problem of information loss caused by the heterogeneity of a virtual array in the prior art. The method comprises the implementation steps: constructing a co-prime array at a receiving end; receiving an incident signal through the co-prime array, and carrying out the modeling; calculating an equivalent virtual signal corresponding to the receiving signal of the co-prime array; constructing an interpolation virtual array, and carrying out the modeling; constructing a multi-sampling snapshot signal of the interpolation virtual array and a sampling covariance matrix; constructing a projection matrix, and defining projection calculation correlated with the projection matrix; designing an optimization problem based on the minimization of the nuclear norm of the signal covariance matrix of the interpolation virtual array, and solving the optimization problem; and carrying out the estimation of the DOA according to the reconstructed covariance matrix of the interpolation virtual array. The method improves the DOA estimation freedom degree and resolution, and can be used for the passive positioning and target detection.

The invention discloses a fast sparse Bayesian learning based direction-of-arrival estimation method and mainly solves the problems of heavy computation and large location estimation error in the prior art. The method includes the implementation steps: (1) adopting antenna receivers to form a uniform linear array; (2) sampling space signals and computing an array covariance matrix R; (3) vectorizing R to obtain a sparse model vector y; (4) dividing space domain grids, and constructing an over-complete base phi(theta) according to the structure of the sparse model vector y; (5) establishing a sparse equation according to the sparse representation relation of the sparse model vector and the over-complete base; (6) defining a hyper-parameter vector alpha, and adopting a fast sparse Bayesian learning algorithm to solve the sparse equation; (7) drawing a magnitude spectrogram according to an optimal estimation value of alpha to obtain a direction-of-arrival value. By the method, estimation accuracy of target reconnaissance and passive location under the conditions of low signal to noise ratio and small snapshot number is improved, computational complexity is lowed, and the method can be applied to target reconnaissance and passive location.

The invention discloses a pulse Doppler radar system based on multiple detection signals and a signal processing method. The pulse Doppler radar system comprises a plurality of transmitters, wherein each transmitter respectively transmits orthogonal pulse detection signals synchronously at different pulse repetition frequencies (PRF), and the PRF of different detection signals meet stagger relationship, the receiving system of airborne radar is composed of a receiver or a plurality of receivers. The signal processing method processes the echo corresponding to different transmission signals via target detection, to obtain respective target detection results. The interference accumulation time of the pulse Doppler radar can be significantly prolonged under single PRF, thereby improving target detection performance. The invention utilizes the stagger relationship among different PRF, to process ambiguity resolution treatment on the detection result having distance and Doppler ambiguity under different PRF, to obtain correct target distance and Doppler information.

The invention discloses a pilot design and synchronous channel estimation method for FBMC / OQAM (Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation). Pilots are inserted at the transmitting end of the FBMC / OQAM system; at a system receiving end, the reversal symmetry of a data column adjacent to a pilot column is used to carry out moving correlation on received signals to determine a starting position; the corresponding relationship between the pilots on the same subcarrier is used in a frequency domain to obtain a frequency offset estimation value, and interference on estimation by the data column adjacent to the pilot column and channel noise is reduced through iteration; after frequency offset compensation, the data column adjacent to the pilot column is firstly assumed to be a zero protected column, pseudo pilots are thus calculated, channel estimation in the frequency domain is then carried out, and data symbols adjacent to the pilot column are then demodulated; and finally, the demodulated data symbols adjacent to the pilot column are used to calculate the pseudo pilots again to estimate the channel. The time offset, the frequency offset and the channel are estimated jointly in the FBMC / OQAM system, and the spectral efficiency is improved, and the estimation performance is also enhanced significantly.

The invention discloses an iterative least square method-based MIMO (multiple input multiple output) radar DOA (direction-of-arrival) estimation method, which is characterized in that receiving and transmitting array response matrixes on which dimension-reduced processing is performed are solved by using an iterative least square method. The iterative least square method-based MIMO radar DOA estimation method comprises the following steps: firstly, performing the dimension-reduced processing on echo data matrixes of multiple radar transmitted pulses and the receiving and transmitting array response matrixes; then, establishing cost functions under the least square condition, and solving the cost functions by utilizing a gradient descent-based iterative method; finally, estimating the direction of a target by utilizing known receiving and transmitting array manifolds. Compared with a traditional monostatic MIMO radar array DOA estimation method, the iterative least square method-based MIMO radar DOA estimation method disclosed by the invention directly obtains the DOA estimation of the target, and does not need to perform spectrum peak search. Noise is effectively suppressed by adopting the dimension-reduced processing, and the estimation accuracy under low signal to noise ratio is improved; the estimation, the inversion and the eigenvalue decomposition operation of high-dimensional data covariance matrixes are avoided; the defects that the calculated amount is high and the needed sample number is large when the traditional array DOA estimation method is applied to a monostatic MIMO radar are overcome.

The disclosed transmission system for mobile digital multimedia broadcast signal comprises: a channel coder to receive, code and interlace data flow to transform it into bit flow; a constellation mapper to map the bit flow into QAM, BPSK or QPSK signal flow; an OFDM signal forming module to insert the continual and discrete pilot frequency into last signal flow and load on the service sub-carrier to form OFDM signal; a framing module to add beacon into the OFDM signal and form transmission frame; and an up-conversion module to generate RF signal for transmission. It also discloses corresponding transmission and allocation method.

The invention provides an information sending and determining and relationship determining method and device. The information sending method comprises the steps that a base station sends M parameter sets through high-level signaling, wherein M>=1, each parameter set at least comprises quasi-colocated nonzero power CSI-RS pilot instruction information, and the quasi-colocated nonzero power CSI-RS pilot instruction information is used for the terminal to acquire the large scale features of the channel; and when M>1, the base station also indicates parameter set selection information of the current subframe for transmitting physical layer control signaling through the physical layer control signaling. With application of the information sending and determining and relationship determining method and device, the terminal is enabled to perform matching according to the acquired large scale features of the channel to acquire the quasi-colocated information of the current data so that the problem in the relevant technologies that the large scale features of the channel acquired by the terminal are inaccurate due to the fact that the indication in the notification signaling in the quasi-colocated information is undefined can be solved and the effect of enhancing the channel estimation performance of the terminal can be achieved.

The invention discloses a method for estimating the signal-to-noise ratio of time-frequency overlapped signals in cognitive radio. The method includes the following steps that: a normalized higher-order cumulant equation is constructed according to the normalized higher-order cumulant of received signals; all component signal modulation type combinations are traversed, the power of component signals is calculated through the normalized higher-order cumulant equation, and whether the modulation type combinations are correct is judged; and correct component signal modulation type combinations and power are obtained, the noise power of the time-frequency overlapped signals is calculated, so that the signal-to-noise ratio of the time-frequency overlapped signals in the underlay cognitive radio can be estimated. According to method, the normalized mean square error of the estimation of the signal-to-noise ratio is smaller than 0.2 under a high spectrum overlap rate when a signal-to-noise ratio is 0dB. The method has excellent performance in the estimation of the signal-to-noise ratio of the time-frequency overlapped signals in the underlay cognitive radio. With the method of the invention adopted, the measurement of interference temperature can be facilitated, primary users and secondary users can coexist under the interference temperature, and therefore, spectrum efficiency can be improved.

The invention discloses an active user detection and channel estimation method with adaptive overhead. Using the estimated active user set and the channel thereof, the estimation quality is evaluatedby calculating the received signal error, and the time slot overhead of the pilot frequency in the frame structure can be adaptively adjusted according to the number of active users and the channel environment in the real system, so that the service quality is ensured with the access time delay as low as possible, and super-reliable active user detection and channel estimation are realized. The method also aims at an enhanced mobile broadband scene, large-scale machine type communication and other huge-address communication scenes in a cellular network in the future. According to the method, the pilot signal for broadband uplink unlicensed multiple access is reasonably designed by utilizing the sporadic characteristic of the uplink transmission flow of the user and the sparsity of a large-scale MIMO virtual angle domain channel, and an advanced compressed sensing technology is introduced, so that the access delay of the user can be greatly reduced.

The invention provides a multiple-target and send-receive angle estimation method of a double-base multiple-input and multiple-output radar. A receiving end collects echo signals of every receiving antenna through an analog to digital (A / D) sampling module. The collected signals passes through a matched filter group, signals corresponding to every launching channel are separated, and receiving data of a virtual array is obtained, wherein the number of array elements is MN. The receiving data is expanded and is transformed into a real number field by utilizing Unitary transformation. A covariance matrix is calculated and is disassembled by utilizing characteristic value to obtain an actual value signal subspace and an actual value signal subspace. In the end, a target DOD is obtained by utilizing Unitary ESPRIT, and a target DOA is obtained by utilizing Unitary Root-MUSIC. According to the multiple-target and send-receive angle estimation method of the double-base multiple-input and multiple-output radar, the send-receive angle is automatically paired, extra pairing operation is not needed, and cross bearing of the target is achieved by utilizing the send-receive angle of the target. The multiple-target and send-receive angle estimation method of the double-base multiple-input and multiple-output radar has the advantages of being high in estimated accuracy and low in computing complexity.

The invention discloses a combined DOA and TOA single-station passive positioning method based on error correction. According to measurement information obtained by a receiving station of an externalradiation source radar system, by introducing an auxiliary variable, a nonlinear equation is converted into a pseudo-linear equation, a pseudo-linear model between the state of a target position and the state of an observation station position is established, an iterative least square method is adopted for estimation, a constrained total least square estimation model is constructed, a constrainedoptimization problem is converted into an unconstrained optimization problem, a Newton iteration method is used for optimization and solution, and the correlation between the auxiliary variable and the target position is used for constructing a correlation least square estimation model, so that the target positioning performance is further improved. The target positioning accuracy is improved through combined estimation of the target position and system errors. Convenience is provided for improving the target positioning performance, the complexity of error registration under the premise of ensuring the estimation performance is reduced, and good positioning performance in the case of large measurement noise is achieved.

The invention relates to a multi-parameter combined estimation method based on bi-static FDA-MIMO radars. The method comprises the following steps: firstly designing a transmitting signal by utilizing characteristics of FDA and MIMO radars; carrying out matched filtering, vectorization and spatial smooth processing on a receiving signal; then estimating a combined steering vector and estimating a DOA and a speed parameter by utilizing an ESPRIT algorithm, and carrying out decoupling and parameter estimation on the DOD and distance information by combining characteristics of a transmitting waveform; and carrying out ambiguity resolution on a distance result estimated by utilizing an ESPRIT algorithm and combining a distance estimated by virtue of a pulse delay estimation algorithm, and carrying out ambiguity resolution on a speed by virtue of an MUSIC algorithm by combining signal characteristics of a large number of pulses. The method provided by the invention has the advantages that the problem that the distance and speed can not be accurately estimated under the condition of a single PRF can be effectively solved, and the estimation of the three-dimensional position and speed of a target can be realized; and a simulation result shows that the method provided by the invention has good estimation accuracy and stability.

The embodiment of the invention provides a channel estimation device and a method thereof. The channel estimation device comprises a receiving pilot signal gaining unit which is used for gaining the receiving pilot signal at the original pilot position from the received signals, a reference pilot signal gaining unit which is used for gaining reference pilot signals, a pilot channel estimation unit which is used for estimating a first channel response according to the receiving pilot signal and the reference pilot signal, an expanding element which is used for expanding the first channel response and gaining a second channel response, and a channel estimation unit which is used for carrying out the channel estimation by the second channel response and the first channel response. The device and the method carry out the channel estimation by the second channel response and the first channel response, increase the density of the initial channel estimation, and improve the performance of channel estimation, thus improving the demodulation performance of the whole system.

The invention discloses a LabVIEW-based (laboratory virtual instrumentation engineering workbench based) microphone array sound source localization method and device. The method includes the steps of building a microphone array; acquiring microphone data signals; calculating differences of time which sound of a sound source takes to reach to microphone sensors at different positions; localizing the sound source according to the differences of time. The method and the device have the advantages that three-dimensional spatial localization of sound sources is achieved by the use of a microphone array, sound source localization precision is improved, interference of uninterested sounds such as noise is effectively inhibited, the differences of time which the sound of the sound source takes to reach to the microphone sensors at the different positions are calculated, calculation complexity is reduced, and timeliness of a pickup system is improved.

The invention belongs to the field of signal processing, and particularly relates to a DOA (Direction of Arrival) estimation method through second-order statistics reconstruction based on matrix completion. Based on the matrix completion theory, the DOA estimation method through second-order statistics reconstruction based on matrix completion is put forward. Firstly, based on the matrix completion method, an elastic regularization factor is introduced to reconstruct a received signal covariance matrix to a noise-free covariance matrix; under the second-order statistics domain, through matrixsummation averaging, a multi-vector problem of the noise-free covariance matrix is converted to a single-vector problem; and finally, a sparse reconstructed weighted l1 norm is used to realize DOA parameter estimation. Non-uniform noise influences can be significantly suppressed, the DOA parameter estimation performance is good, and in a condition of a low signal-to-noise ratio, the provided algorithm has high angle estimation precision and high resolution.

The invention discloses a carrier synchronization method of an MPSK system based on maximum likelihood estimation, belonging to the technical field of the modulation and the demodulation of digital communication and comprising the following steps: firstly, eliminating the modulation information of a receiving signal to obtain a single carrier only polluted by noises; then, utilizing a fast search algorithm based on dichotomy to obtain maximum likelihood estimation values of frequency deviation and phase deviation; and then, compensating an original receiving signal by the maximum likelihood estimation values to complete carrier synchronization and demodulation, wherein the estimation and compensation method needs to be continuously used for tracking the carrier synchronization in the demodulation process. A simulation result shows that the carrier synchronization method has very good property approximated to the Cramer-Rao lower bound, very little calculation amount and very wide frequency deviation estimation range and is a practical carrier synchronization method.

The invention discloses a nonlinear system state estimation method based on Kalman filtering positioning, and proposes a strongly adaptive Kalman filtering mechanism which combines a nonlinear filtering algorithm and Kalman filtering. The method comprises the steps: carrying out the simultaneous estimation of node positions and channel parameters through employing an RSSI state estimation algorithm based on square root volume Kalman filtering, and obtaining the estimation value of a state vector; employing the Kalman filtering for further processing according to the linear change of a state equation, obtaining optimal estimation, and building a strongly adaptive square root volume Kalman filtering algorithm; giving the design steps of the strongly adaptive square root volume Kalman filtering algorithm; and calculating a theoretical square root error lower bound under a state space model based on the RSSI state estimation. The method enables an estimation result to be improved, and improves the precision. The method does not need to excessively depend on improper initial conditions, can be well adapted to a highly nonlinear system, and is not liable to enable the algorithm to be divergent and ineffective.

Provided are a synchronization apparatus and method for improving timing estimation performance in an OFDM-FDMA / CDMA / TDMA system, which can correctly estimate symbol timing through a more correct timing metric using a guard interval of a preamble. The synchronization apparatus includes an auto-correlator for calculating an auto-correlation value of a received signal and a signal delayed by a predetermined time, a power detector for calculating power of the received signal, a timing metric / normalizer for normalizing the auto-correlation value by dividing the auto-correlation value by the calculated power to obtain a timing metric, and a peak detector for finding a peak value of the timing metric to estimate a frame starting position and an initial symbol timing. The auto-correlator calculates an auto-correlation length as long as a length of a guard interval, considering the preamble characteristic that the patterns are repeated in the time domain. The initial symbol timing is set to a position determined by adding the position where the timing metric has a peak value to the length of the guard interval and subtracting the maximum value of the expected channel delay spread from the result value.