CN106510988A - Intelligent wheelchair supporting intelligent terminal mechanical structure - Google Patents

Abstract

The invention discloses an intelligent wheelchair supporting an intelligent terminal mechanical structure. The intelligent wheelchair is provided with an intelligent terminal, an automobile data recorder, a voice control module, a distance sensing module, a display terminal and a main control computer; the intelligent terminal is in wired or wireless communication with the main control computer and used for processing input signals of the main control computer; the automobile data recorder is used for recording image and sound information obtained in the driving process of the wheelchair; the voice control module is used for inputting a voice instruction of an operator and transmitting the voice instruction to the intelligent terminal for processing; the distance sensing module is used for detecting physical variation of an object and measuring the distance between a sensor and the object; the display terminal is used for displaying the signals processed by the intelligent terminal; the main control computer is in wired communication with the automobile data recorder, the voice control module, the distance sensing module and the display terminal, processes the input signals and displays the input signals. According to the intelligent wheelchair, the operation reliability and the using safety of the wheelchair are improved; the intelligent terminal, the voice control module and the distance sensing module increase the intelligent level of the wheelchair and are beneficial for improving the wheelchair walking safety and reliability.

Description

A kind of intelligent wheel chair for supporting intelligent terminal machinery structure

Technical field

The invention belongs to intelligent wheel chair technical field, more particularly to a kind of intelligence wheel for supporting intelligent terminal machinery structure Chair.

Background technology

Existing wheelchair, wheelchair are the important tools of rehabilitation, and it is not only the walking-replacing tool of limbs the disabled, prior It is them is carried out physical exercise by means of wheelchair and is participated in social activities.Common wheelchair is typically by wheelchair frame, wheel, brake dress Put and seat against four parts composition.Hand wheelchair increases manual setter on the basis of common wheelchair.Including walking, the lamp in building is climbed Tool is fixing seat mode, it is impossible to which prostration uprightly can not rise, and can not be rotated.Also no intelligent terminal has been solved more The control for overflowing and service, further facilitate those to need depth to help and more multi-functional so this wheelchair will not bring Disabled person.

Existing Wheelchair structure is simple, and intelligence degree is relatively low, and safety and reliability is poor.

The content of the invention

It is an object of the invention to provide a kind of intelligent wheel chair for supporting intelligent terminal machinery structure, it is intended to solve existing Wheelchair structure is simple, and intelligence degree is relatively low, the poor problem of safety and reliability.

The present invention is achieved in that a kind of intelligent wheel chair for supporting intelligent terminal machinery structure, and the support intelligence is eventually The intelligent wheel chair of end frame for movement includes：

Intelligent terminal, with the wired or wireless communication of main control computer, realizes the process to main control computer input signal；

Drive recorder, for recording the related information such as image and sound in wheelchair traveling way；

Speech control module, for the phonetic order of input operation person, and delivers to intelligent terminal and is processed, realize wheelchair The Voice command of frame for movement；

Apart from induction module, for the physical change amount of detection object thing, by the variable quantity is scaled distance, survey Distance of the amount from sensor to object；

Display terminal, for showing to the signal that intelligent terminal is processed, refers to for operator；

Main control computer, with drive recorder, speech control module, apart from induction module, display terminal wire communication, realize row Car recorder, speech control module, apart from the process of induction module input signal, and show in display terminal.

Further, the intelligent terminal is additionally provided with GPS module, 4G modules and WIFI module；

GPS module realizes the positioning of wheelchair；

4G modules and WIFI module realize the communication of intelligent terminal and other-end and main control computer.

Further, the intelligent terminal is provided with synchronized orthogonal Frequency Hopping Signal blind source separating module, and the synchronized orthogonal is jumped The synchronized orthogonal Frequency Hopping Signal blind source separation method of frequency signal blind source separating module includes：

Step one, utilizes the array antenna received containing M array element from the Frequency Hopping Signal of multiple synchronized orthogonal frequency hopping radio sets, right Sampled per signal is received all the way, the M roads discrete time-domain mixed signal after being sampled

Step 2, carries out overlapping adding window Short Time Fourier Transform to M roads discrete time-domain mixed signal, obtains M mixing letter Number time-frequency domain matrixP=0,1 ..., P-1, q=0,1 ..., N_fft- 1, wherein P tables Show total window number, N_fftRepresent FFT length；(p, q) represents time-frequency index, and specific time-frequency value is Here N_fftThe length of FFT is represented, p represents adding window number of times, T_sRepresent sampling interval, f_sSample frequency is represented, C is integer, Represent the sampling number at Short Time Fourier Transform adding window interval, C ＜ N_fft, and K_c=N_fft/ C is integer, that is to say, that employing It is the Short Time Fourier Transform for overlapping adding window；

Step 3, to the frequency-hopping mixing signal time-frequency domain matrix obtained in step 2 Pre-processed；

Step 4, estimates the jumping moment of each jump using clustering algorithm and respectively jumps corresponding normalized hybrid matrix Column vector, Hopping frequencies are at p (p=0,1,2 ... the P-1) moment, rightThe frequency values of expression are clustered, in the cluster for obtaining Heart numberThe carrier frequency number that the expression p moment is present,Individual cluster centre then represents the size of carrier frequency, uses respectivelyRepresent；To each sampling instant p (p=0,1,2 ... P-1), using clustering algorithm pairEnter Row cluster, it is same availableIndividual cluster centre, usesRepresent；To allAverage and round, obtain To the estimation of source signal numberI.e.

Find outMoment, use p_hRepresent, the p to each section of continuous value_hIntermediate value is sought, is usedTable Show that l sections are connected p_hIntermediate value, thenRepresent the estimation at l-th frequency hopping moment；

Obtained according to estimationAnd the 4th estimate frequency hopping moment for obtaining in step Estimate each jump correspondingIndividual hybrid matrix column vectorSpecifically formula is：

HereRepresent that l is jumped correspondingIndividual mixing Matrix column vector estimate；Estimate the corresponding carrier frequency of each jump, useRepresent that l jumps correspondence 'sIndividual frequency estimation, computing formula are as follows：

According to step 4, step 5, estimates that the normalization hybrid matrix column vector for obtaining estimates time-frequency domain frequency hopping source signal；

Step 6, splices to the time-frequency domain frequency hopping source signal between different frequency hopping points；Estimate that l is jumped correspondingIt is individual Incident angle, usesThe corresponding incident angle of l n-th source signal of jump is represented,Computing formula it is as follows：

Represent that l jumps n-th hybrid matrix column vector for estimating to obtainM-th element, c represents the light velocity, That is v_c=3 × 10⁸Meter per second；Judge that l (l=2,3 ...) jumps the source signal and first estimated and jumps right between the source signal estimated Should be related to, judgment formula is as follows：

Wherein m_n ^(l)Represent that l jumps the m for estimating_n ^(l)Individual signal and first n-th signal for jumping estimation belong to same source Signal；By different frequency hopping point estimation to the signal for belonging to same source signal be stitched together, as final time-frequency domain source Signal estimation, uses Y_n(p, q) expression time-frequency domain estimate of n-th source signal in time frequency point (p, q), p=0,1,2 ...., P, q=0,1,2 ..., N_fft- 1, i.e.,：

Step 7, according to source signal time-frequency domain estimate, recovers time domain frequency hopping source signal, to each sampling instant p (p= 0,1,2 ...) frequency domain data Y_n(p, q), q=0,1,2 ..., N_fft- 1 is N_fftThe IFFT conversion of point, obtains p sampling instants pair The time domain frequency hopping source signal answered, uses y_n(p,q_t)(q_t=0,1,2 ..., N_fft- 1) represent；The time domain that above-mentioned all moment are obtained Frequency hopping source signal y_n(p,q_t) process is merged, final time domain frequency hopping synthesizer Signal estimation is obtained, concrete formula is as follows：

Here K_c=N_fftThe sampling number of/C, C for Short Time Fourier Transform adding window interval, N_fftFor the length of FFT.

Further, the main control computer is provided with digital signal modulated module, the numeral letter of the digital signal modulated module Number processing method includes：

Receive signal y (t) to be expressed as：

Y (t)=x (t)+n (t)；

Wherein, x (t) is digital modulation signals, and n (t) is the impulsive noise of obedience standard S α S distributions, for MASK and MPSK is modulated, and the analytical form of x (t) is expressed as：

Wherein, N is sampling number, a_nFor the information symbol for sending, in MASK signals, a_n=0,1,2 ..., M-1, M are Order of modulation, in mpsk signal, a_n=e^j2πε/M, ε=0,1,2 ..., M-1, g (t) represent rectangle shaping pulse, T_bRepresent symbol Number cycle, f_cRepresent carrier frequency, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；Adjust for MFSK System, the analytical form of x (t) are expressed as：

Wherein, f_mFor the side-play amount of m-th carrier frequency, if MFSK signals carrier shift is Δ f, f_m=-(M-1) Δ f ,- (M-3) Δ f ..., (M-3) Δ f, (M-1) Δ f, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；

There is no the expression formula of closing in the probability density function of Alpha Stable distritations, describe which with following characteristic function Distribution character：

WhereinFor sign function,

α (0 ＜ α≤2) is characterized index, and γ is the coefficient of dispersion, and β is symmetric parameter, and ζ is location parameter.When ζ=0, β=0 And during γ=1, the distribution is referred to as standard S α S distributions；

The fractional lower-order ambiguity function of digital modulation signals x (t) is expressed as：

Wherein, τ is delay skew, and f is Doppler frequency shift, 0 ＜ a, b ＜ α/2；x^*T () represents the conjugation of x (t).As x (t) For real signal when, x (t)^{＜ p ＞}=| x (t) |^{＜ p ＞}sgn(x(t))；When x (t) is time multiplexed signal, [x (t)]^{＜ p ＞}=| x (t) |^p-1x^* T (), the nonlinear operation only change the amplitude information of signal, retain its frequency and phase information, effective impulse noise mitigation.

Further, the main control computer is provided with energy detection module, the energy detection method bag of the energy detection module Include：

Radio frequency or intermediate-freuqncy signal are obtained signal x1 with single-frequency mixing using frequency mixer by the first step；

Second step, removes the high fdrequency component of signal x1 using low pass filter A, and the three dB bandwidth of low pass filter A is more than divides Analysis bandwidth B s, obtains signal x2, and now x2 is the signal of zero intermediate frequency, and the signal with a width of Bs is affected by wave filter A Very little, it is negligible；

Signal x2 is carried out two step process by the 3rd step simultaneously：First by x2 by low pass filter B, passband is 0--PBs, P<1, the low-frequency time-domain signal x2L of signal is obtained with a width of PBs；Again by x2 by high-pass filter, passband is PBs-Bs, The high frequency time-domain signal x2H of signal is obtained with a width of (1-P) Bs；

4th step, is added up using time domain, i.e. the quadratic sum of the mould of time-domain signal, obtains the energy value EL of signal x2L, and The energy value EH of signal x2H；

5th step, tries to achieve ratio R=EL/EH；

6th step, thresholding are demarcated, and the data to having signal and no signal are repeatedly sought R values first, by statistical probability Obtain thresholding C1 and C2, C2>The size of C1, C2 value mainly affects the size of false dismissal probability, C1 mainly to affect false alarm probability, selected The thresholding selected should ensure that the unfavorable factor of both the above is possible little；

7th step, the renewal of flag bit flag, flag=0 represent a front testing result for no signal, this kind of condition Under, only work as R>It is judged to currently detected signal during C2, flag is changed into 1；Work as flag=1, represent that a front testing result is Have a signal, it is this kind of under the conditions of, only work as R<It is judged to currently be not detected by signal during C1, flag is changed into 0；

According to flag bit, 8th step, controls whether subsequent demodulation thread etc. is opened：Flag=1, opens subsequent demodulation thread Deng, otherwise close subsequent demodulation thread.

The present invention provide support intelligent terminal machinery structure intelligent wheel chair, be provided with intelligent terminal, drive recorder, Speech control module and apart from induction module, improves the reliability of operation, improves the safety in utilization of wheelchair；Intelligence is eventually End, speech control module and the intelligent level of wheelchair is improve apart from induction module, be conducive to improving peace when wheelchair is walked Full property and reliability.

Description of the drawings

Fig. 1 is the intelligent wheel chair structural representation for supporting intelligent terminal machinery structure provided in an embodiment of the present invention；

In figure：1st, intelligent terminal；2nd, drive recorder；3rd, speech control module；4th, apart from induction module；5th, show eventually End；6th, main control computer.

Specific embodiment

In order that the objects, technical solutions and advantages of the present invention become more apparent, with reference to embodiments, to the present invention It is further elaborated.It should be appreciated that specific embodiment described herein is not used to only to explain the present invention Limit the present invention.

Below in conjunction with the accompanying drawings the structure of the present invention is explained in detail.

As shown in figure 1, the intelligent wheel chair of the support intelligent terminal machinery structure of the embodiment of the present invention includes：Intelligent terminal 1, Drive recorder 2, speech control module 3, apart from induction module 4, display terminal 5, main control computer 6.

Intelligent terminal 1, with the wired or wireless communication of main control computer, realizes the process to main control computer input signal.

Drive recorder 2, for recording the related information such as image and sound in wheelchair traveling way.

Speech control module 3, for the phonetic order of input operation person, and delivers to intelligent terminal 1 and is processed, and realizes wheel The Voice command of chair frame for movement.

Apart from induction module 4, for the physical change amount of detection object thing, by the variable quantity is scaled distance, come Distance of the measurement from sensor to object.

Display terminal 5, for showing to the signal that intelligent terminal 1 is processed, refers to for operator；

Main control computer 6, with drive recorder 2, speech control module 3, apart from induction module 4,5 wire communication of display terminal, Realize drive recorder 2, speech control module 3, apart from the process of 4 input signal of induction module, and show in display terminal 5.

Intelligent terminal 1 is additionally provided with GPS module, 4G modules and WIFI module；GPS module realizes the positioning of wheelchair；4G moulds Block and WIFI module realize the communication of intelligent terminal 1 and other-end and main control computer 6.

Further, the intelligent terminal is provided with synchronized orthogonal Frequency Hopping Signal blind source separating module, and the synchronized orthogonal is jumped The synchronized orthogonal Frequency Hopping Signal blind source separation method of frequency signal blind source separating module includes：

Step one, utilizes the array antenna received containing M array element from the Frequency Hopping Signal of multiple synchronized orthogonal frequency hopping radio sets, right Sampled per signal is received all the way, the M roads discrete time-domain mixed signal after being sampled

Step 2, carries out overlapping adding window Short Time Fourier Transform to M roads discrete time-domain mixed signal, obtains M mixing letter Number time-frequency domain matrixP=0,1 ..., P-1, q=0,1 ..., N_fft- 1, wherein P is represented Total window number, N_fftRepresent FFT length；(p, q) represents time-frequency index, and specific time-frequency value is Here N_fftThe length of FFT is represented, p represents adding window number of times, T_sRepresent sampling interval, f_sSample frequency is represented, C is integer, Represent the sampling number at Short Time Fourier Transform adding window interval, C ＜ N_fft, and K_c=N_fft/ C is integer, that is to say, that employing It is the Short Time Fourier Transform for overlapping adding window；

Step 3, to the frequency-hopping mixing signal time-frequency domain matrix obtained in step 2 Pre-processed；

Step 4, estimates the jumping moment of each jump using clustering algorithm and respectively jumps corresponding normalized hybrid matrix Column vector, Hopping frequencies are at p (p=0,1,2 ... the P-1) moment, rightThe frequency values of expression are clustered, in the cluster for obtaining Heart numberThe carrier frequency number that the expression p moment is present,Individual cluster centre then represents the size of carrier frequency, uses respectivelyRepresent；To each sampling instant p (p=0,1,2 ... P-1), using clustering algorithm pairEnter Row cluster, it is same availableIndividual cluster centre, usesRepresent；To allAverage and round, obtain The estimation of source signal numberI.e.

Find outMoment, use p_hRepresent, the p to each section of continuous value_hIntermediate value is sought, is usedTable Show that l sections are connected p_hIntermediate value, thenRepresent the estimation at l-th frequency hopping moment；

Obtained according to estimationAnd the 4th estimate frequency hopping moment for obtaining in step Estimate each jump correspondingIndividual hybrid matrix column vectorSpecifically formula is：

HereRepresent that l is jumped correspondingIndividual mixing Matrix column vector estimate；Estimate the corresponding carrier frequency of each jump, useRepresent that l jumps correspondence 'sIndividual frequency estimation, computing formula are as follows：

According to step 4, step 5, estimates that the normalization hybrid matrix column vector for obtaining estimates time-frequency domain frequency hopping source signal；

Step 6, splices to the time-frequency domain frequency hopping source signal between different frequency hopping points；Estimate that l is jumped correspondingIt is individual Incident angle, usesThe corresponding incident angle of l n-th source signal of jump is represented,Computing formula it is as follows：

Represent that l jumps n-th hybrid matrix column vector for estimating to obtainM-th element, c represents the light velocity, That is v_c=3 × 10⁸Meter per second；Judge that l (l=2,3 ...) jumps the source signal and first estimated and jumps right between the source signal estimated Should be related to, judgment formula is as follows：

Wherein m_n ^(l)Represent that l jumps the m for estimating_n ^(l)Individual signal and first n-th signal for jumping estimation belong to same source Signal；By different frequency hopping point estimation to the signal for belonging to same source signal be stitched together, as final time-frequency domain source Signal estimation, uses Y_n(p, q) expression time-frequency domain estimate of n-th source signal in time frequency point (p, q), p=0,1,2 ...., P, q=0,1,2 ..., N_fft- 1, i.e.,：

Step 7, according to source signal time-frequency domain estimate, recovers time domain frequency hopping source signal, to each sampling instant p (p= 0,1,2 ...) frequency domain data Y_n(p, q), q=0,1,2 ..., N_fft- 1 is N_fftThe IFFT conversion of point, obtains p sampling instants pair The time domain frequency hopping source signal answered, uses y_n(p,q_t)(q_t=0,1,2 ..., N_fft- 1) represent；The time domain that above-mentioned all moment are obtained Frequency hopping source signal y_n(p,q_t) process is merged, final time domain frequency hopping synthesizer Signal estimation is obtained, concrete formula is as follows：

Here K_c=N_fftThe sampling number of/C, C for Short Time Fourier Transform adding window interval, N_fftFor the length of FFT.

Further, the main control computer is provided with digital signal modulated module, the numeral letter of the digital signal modulated module Number processing method includes：

Receive signal y (t) to be expressed as：

Y (t)=x (t)+n (t)；

Wherein, x (t) is digital modulation signals, and n (t) is the impulsive noise of obedience standard S α S distributions, for MASK and MPSK is modulated, and the analytical form of x (t) is expressed as：

Wherein, N is sampling number, a_nFor the information symbol for sending, in MASK signals, a_n=0,1,2 ..., M-1, M are Order of modulation, in mpsk signal, a_n=e^j2πε/M, ε=0,1,2 ..., M-1, g (t) represent rectangle shaping pulse, T_bRepresent symbol Number cycle, f_cRepresent carrier frequency, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；Modulate for MFSK, The analytical form of x (t) is expressed as：

Wherein, f_mFor the side-play amount of m-th carrier frequency, if MFSK signals carrier shift is Δ f, f_m=-(M-1) Δ f ,- (M-3) Δ f ..., (M-3) Δ f, (M-1) Δ f, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；

There is no the expression formula of closing in the probability density function of Alpha Stable distritations, describe which with following characteristic function Distribution character：

WhereinFor sign function,

α (0 ＜ α≤2) is characterized index, and γ is the coefficient of dispersion, and β is symmetric parameter, and ζ is location parameter.When ζ=0, β=0 And during γ=1, the distribution is referred to as standard S α S distributions；

The fractional lower-order ambiguity function of digital modulation signals x (t) is expressed as：

Wherein, τ is delay skew, and f is Doppler frequency shift, 0 ＜ a, b ＜ α/2；x^*T () represents the conjugation of x (t).As x (t) For real signal when, x (t)^{＜ p ＞}=| x (t) |^{＜ p ＞}sgn(x(t))；When x (t) is time multiplexed signal, [x (t)]^{＜ p ＞}=| x (t) |^p-1x^* T (), the nonlinear operation only change the amplitude information of signal, retain its frequency and phase information, effective impulse noise mitigation.

Further, the main control computer is provided with energy detection module, the energy detection method bag of the energy detection module Include：

Radio frequency or intermediate-freuqncy signal are obtained signal x1 with single-frequency mixing using frequency mixer by the first step；

Second step, removes the high fdrequency component of signal x1 using low pass filter A, and the three dB bandwidth of low pass filter A is more than divides Analysis bandwidth B s, obtains signal x2, and now x2 is the signal of zero intermediate frequency, and the signal with a width of Bs is affected by wave filter A Very little, it is negligible；

Signal x2 is carried out two step process by the 3rd step simultaneously：First by x2 by low pass filter B, passband is 0--PBs, P<1, the low-frequency time-domain signal x2L of signal is obtained with a width of PBs；Again by x2 by high-pass filter, passband is PBs-Bs, The high frequency time-domain signal x2H of signal is obtained with a width of (1-P) Bs；

4th step, is added up using time domain, i.e. the quadratic sum of the mould of time-domain signal, obtains the energy value EL of signal x2L, and The energy value EH of signal x2H；

5th step, tries to achieve ratio R=EL/EH；

6th step, thresholding are demarcated, and the data to having signal and no signal are repeatedly sought R values first, by statistical probability Obtain thresholding C1 and C2, C2>The size of C1, C2 value mainly affects the size of false dismissal probability, C1 mainly to affect false alarm probability, selected The thresholding selected should ensure that the unfavorable factor of both the above is possible little；

7th step, the renewal of flag bit flag, flag=0 represent a front testing result for no signal, this kind of condition Under, only work as R>It is judged to currently detected signal during C2, flag is changed into 1；Work as flag=1, represent that a front testing result is Have a signal, it is this kind of under the conditions of, only work as R<It is judged to currently be not detected by signal during C1, flag is changed into 0；

According to flag bit, 8th step, controls whether subsequent demodulation thread etc. is opened：Flag=1, opens subsequent demodulation thread Deng, otherwise close subsequent demodulation thread.

The operation principle of the present invention：

Intelligent terminal and the wired or wireless communication of main control computer, the process to main control computer input signal；Drive recorder is recorded The related information such as image and sound in wheelchair traveling way；The phonetic order of speech control module input operation person, and deliver to Intelligent terminal is processed, and realizes the Voice command of wheelchair frame for movement；Apart from the physical change of induction module detection object thing Amount, by the variable quantity is scaled distance, measures the distance from sensor to object；Display terminal is to intelligent terminal Signal shows, refers to for operator；Main control computer realizes drive recorder, speech control module, apart from induction module input signal Process, and show in display terminal.

Presently preferred embodiments of the present invention is the foregoing is only, not to limit the present invention, all essences in the present invention Any modification, equivalent and improvement made within god and principle etc., should be included within the scope of the present invention.

Claims (5)

1. a kind of intelligent wheel chair for supporting intelligent terminal machinery structure, it is characterised in that support intelligent terminal machinery structure Intelligent wheel chair include：

Intelligent terminal, with the wired or wireless communication of main control computer, realizes the process to main control computer input signal；

Drive recorder, the information related for recording image and sound in wheelchair traveling way；

Speech control module, for the phonetic order of input operation person, and delivers to intelligent terminal and is processed, and realizes wheelchair machinery The Voice command of structure；

Apart from induction module, for the physical change amount of detection object thing, by the variable quantity is scaled distance, measure from Distance of the sensor to object；

Display terminal, for showing to the signal that intelligent terminal is processed, refers to for operator；

Main control computer, with drive recorder, speech control module, apart from induction module, display terminal wire communication, realize driving note Record instrument, speech control module, apart from the process of induction module input signal, and show in display terminal.

2. the intelligent wheel chair of intelligent terminal machinery structure is supported as claimed in claim 1, it is characterised in that the intelligent terminal It is additionally provided with GPS module, 4G modules and WIFI module；

GPS module realizes the positioning of wheelchair；

4G modules and WIFI module realize the communication of intelligent terminal and other-end and main control computer.

3. the intelligent wheel chair of intelligent terminal machinery structure is supported as claimed in claim 1, it is characterised in that the intelligent terminal It is provided with synchronized orthogonal Frequency Hopping Signal blind source separating module, the synchronized orthogonal of the synchronized orthogonal Frequency Hopping Signal blind source separating module Frequency Hopping Signal blind source separation method includes：

Step one, utilizes the array antenna received containing M array element from the Frequency Hopping Signal of multiple synchronized orthogonal frequency hopping radio sets, to each Road receives signal and is sampled, the M roads discrete time-domain mixed signal after being sampled

Step 2, carries out overlapping adding window Short Time Fourier Transform to M roads discrete time-domain mixed signal, obtains M mixed signal Time-frequency domain matrix

P=0,1 ..., P-1, q=0,1 ..., N_fft- 1, wherein P represent total window number, N_fftRepresent FFT length；(p, q) Time-frequency index is represented, specific time-frequency value isHere N_fftThe length of FFT is represented, p represents adding window Number of times, T_sRepresent sampling interval, f_sSample frequency is represented, C is integer, represent the sampled point at Short Time Fourier Transform adding window interval Number, C ＜ N_fft, and K_c=N_fft/ C is integer, that is to say, that use the Short Time Fourier Transform for overlapping adding window；

Step 3, to the frequency-hopping mixing signal time-frequency domain matrix obtained in step 2

Pre-processed；

Step 4, using clustering algorithm estimate each jump jumping moment and respectively jump corresponding normalized mixed moment array to Amount, Hopping frequencies are at p (p=0,1,2 ... the P-1) moment, rightThe frequency values of expression are clustered, the cluster centre number for obtainingThe carrier frequency number that the expression p moment is present,Individual cluster centre then represents the size of carrier frequency, uses respectively Represent；To each sampling instant p (p=0,1,2 ... P-1), using clustering algorithm pairClustered, it is same availableIndividual cluster centre, usesRepresent；To allAverage and round, obtain the estimation of source signal numberI.e.

$\hat{N}=round\left(\frac{1}{p}\underset{p=0}{\overset{P-1}{\&Sigma;}}{\hat{N}}_p\right);$

Find outMoment, use p_hRepresent, the p to each section of continuous value_hIntermediate value is sought, is usedRepresent the L sections are connected p_hIntermediate value, thenRepresent the estimation at l-th frequency hopping moment；

Obtained according to estimationAnd the 4th estimate that the frequency hopping moment for obtaining estimates in step It is each to jump correspondingIndividual hybrid matrix column vectorSpecifically formula is：

${\hat{a}}_n\left(l\right)=\left\{\begin{array}{cc}\frac{1}{{\stackrel{\&OverBar;}{p}}_h\left(1\right)}\&CenterDot;\underset{p=1,p\&NotEqual;p_h}{\overset{{\stackrel{\&OverBar;}{p}}_h\left(1\right)}{\&Sigma;}}{b}_{n,p}^0& l=1,\\ \frac{1}{{\stackrel{\&OverBar;}{p}}_h\left(l\right)-{\stackrel{\&OverBar;}{p}}_h(l-1)}\&CenterDot;\underset{p={\stackrel{\&OverBar;}{p}}_h(l-1)+1,p\&NotEqual;p_h}{\overset{{\stackrel{\&OverBar;}{p}}_h\left(l\right)}{\&Sigma;}}{b}_{n,p}^0& l>1,\end{array}\right.,n=1,2,\mathrm{...},\hat{N}$

HereRepresent that l is jumped correspondingIndividual mixed moment array Vectorial estimate；Estimate the corresponding carrier frequency of each jump, useRepresent that l is jumped correspondingIt is individual Frequency estimation, computing formula are as follows：

${\hat{f}}_{c,n}\left(l\right)=\left\{\begin{array}{cc}\frac{1}{{\stackrel{\&OverBar;}{p}}_h\left(1\right)}\&CenterDot;\underset{p=1,p\&NotEqual;p_h}{\overset{{\stackrel{\&OverBar;}{p}}_h\left(1\right)}{\&Sigma;}}{f}_o^n\left(p\right)& l=1,\\ \frac{1}{{\stackrel{\&OverBar;}{p}}_h\left(l\right)-{\stackrel{\&OverBar;}{p}}_h(l-1)}\&CenterDot;\underset{p={\stackrel{\&OverBar;}{p}}_h(l-1)+1,p\&NotEqual;p_h}{\overset{{\stackrel{\&OverBar;}{p}}_h\left(l\right)}{\&Sigma;}}{f}_o^n\left(p\right)& l>1,\end{array}\right.,n=1,2,\mathrm{...},\hat{N};$

According to step 4, step 5, estimates that the normalization hybrid matrix column vector for obtaining estimates time-frequency domain frequency hopping source signal；

Step 6, splices to the time-frequency domain frequency hopping source signal between different frequency hopping points；Estimate that l is jumped correspondingIndividual incidence Angle, usesThe corresponding incident angle of l n-th source signal of jump is represented,Computing formula it is as follows：

${\widehat{\mathrm{\&theta;}}}_n\left(l\right)=\frac{1}{M-1}\underset{m=2}{\overset{M}{\&Sigma;}}{\sin }^{-1}\&lsqb;\frac{angle\left({\hat{a}}_{n,m}\right(l)/{\hat{a}}_{n,m-1}\left(l\right))*c}{2\mathrm{\&pi;}{\hat{f}}_{c,n}\left(l\right)d}\&rsqb;,n=1,2,\mathrm{...},\hat{N};$

Represent that l jumps n-th hybrid matrix column vector for estimating to obtainM-th element, c represents the light velocity, i.e. v_c =3 × 10⁸Meter per second；Judge that l (l=2,3 ...) jumps the source signal estimated and jumps corresponding between the source signal estimated with first Relation, judgment formula are as follows：

${m_n}^{\left(l\right)}=\underset{m}{\arg \min }|{\widehat{\mathrm{\&theta;}}}_m^{\left(l\right)}-{\widehat{\mathrm{\&theta;}}}_n^{\left(1\right)}|,n=1,2,\mathrm{...},\hat{N};$

Wherein m_n ^(l)Represent that l jumps the m for estimating_n ^(l)Individual signal and first n-th signal for jumping estimation belong to same source letter Number；By different frequency hopping point estimation to the signal for belonging to same source signal be stitched together, believe as final time-frequency domain source Number estimate, use Y_n(p, q) expression time-frequency domain estimate of n-th source signal in time frequency point (p, q), p=0,1,2 ...., P, Q=0,1,2 ..., N_fft- 1, i.e.,：

Step 7, according to source signal time-frequency domain estimate, recovers time domain frequency hopping source signal, to each sampling instant p (p=0,1, 2 ...) frequency domain data Y_n(p, q), q=0,1,2 ..., N_fft- 1 is N_fftThe IFFT conversion of point, obtains p sampling instants corresponding Time domain frequency hopping source signal, uses y_n(p,q_t) (q_t=0,1,2 ..., N_fft- 1) represent；The time domain obtained to above-mentioned all moment is jumped Frequency source signal y_n(p,q_t) process is merged, final time domain frequency hopping synthesizer Signal estimation is obtained, concrete formula is as follows：

$s_n\&lsqb;kC:(k+1)C-1\&rsqb;=\left\{\begin{array}{cc}\underset{m=0}{\overset{k}{\&Sigma;}}{y}_n\&lsqb;m,(k-m)C:(k-m+1)C-1\&rsqb;& k<K_c\\ \underset{m=k-K_c+1}{\overset{k}{\&Sigma;}}{y}_n\&lsqb;m,(k-m)C:(k-m+1)C-1\&rsqb;& k\&GreaterEqual;K_c\end{array}\right.,k=0,1,2,\mathrm{...}$

Here K_c=N_fftThe sampling number of/C, C for Short Time Fourier Transform adding window interval, N_fftFor the length of FFT.

4. the intelligent wheel chair of intelligent terminal machinery structure is supported as claimed in claim 1, it is characterised in that the main control computer sets Digital signal modulated module is equipped with, the digital signal processing method of the digital signal modulated module includes：

Receive signal y (t) to be expressed as：

Y (t)=x (t)+n (t)；

Wherein, x (t) is digital modulation signals, and n (t) is the impulsive noise of obedience standard S α S distributions, is adjusted for MASK and MPSK System, the analytical form of x (t) are expressed as：

Wherein, N is sampling number, a_nFor the information symbol for sending, in MASK signals, a_n=0,1,2 ..., M-1, M are modulation Exponent number, in mpsk signal, a_n=e^j2πε/M, ε=0,1,2 ..., M-1, g (t) represent rectangle shaping pulse, T_bRepresent symbol week Phase, f_cRepresent carrier frequency, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；Modulate for MFSK, x T the analytical form of () is expressed as：

Wherein, f_mFor the side-play amount of m-th carrier frequency, if MFSK signals carrier shift is Δ f, f_m=-(M-1) Δ f ,-(M-3) Δ f ..., (M-3) Δ f, (M-1) Δ f, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；

There is no the expression formula of closing in the probability density function of Alpha Stable distritations, its distribution is described with following characteristic function Characteristic：

WhereinFor sign function,

α (0 ＜ α≤2) is characterized index, and γ is the coefficient of dispersion, and β is symmetric parameter, and ζ is location parameter, as ζ=0, β=0 and γ When=1, the distribution is referred to as standard S α S distributions；

The fractional lower-order ambiguity function of digital modulation signals x (t) is expressed as：

$\mathrm{\&chi;}(\mathrm{\&tau;},f)={\&Integral;}_{-\mathrm{\&infin;}}^{\mathrm{\&infin;}}{\&lsqb;x(t+\mathrm{\&tau;}/2)\&rsqb;}^{<a>}{\&lsqb;x^{*}(t-\mathrm{\&tau;}/2)\&rsqb;}^{<b>}{e}^{-j2\mathrm{\&pi;}ft}dt;$

Wherein, τ is delay skew, and f is Doppler frequency shift, 0 ＜ a, b ＜ α/2；x^*T () represents the conjugation of x (t)；When x (t) is reality During signal, x (t)^{＜ p ＞}=| x (t) |^{＜ p ＞}sgn(x(t))；When x (t) is time multiplexed signal, [x (t)]^{＜ p ＞}=| x (t) |^p-1x^*(t), The nonlinear operation only changes the amplitude information of signal, retains its frequency and phase information, effective impulse noise mitigation.

5. the intelligent wheel chair of intelligent terminal machinery structure is supported as claimed in claim 1, it is characterised in that the main control computer sets Energy detection module is equipped with, the energy detection method of the energy detection module includes：

Radio frequency or intermediate-freuqncy signal are obtained signal x1 with single-frequency mixing using frequency mixer by the first step；

Second step, removes the high fdrequency component of signal x1 using low pass filter A, and the three dB bandwidth of low pass filter A is more than analytic band Wide Bs, obtains signal x2, and now x2 is the signal of zero intermediate frequency, and the signal with a width of Bs is affected very little by wave filter A, It is negligible；

Signal x2 is carried out two step process by the 3rd step simultaneously：First by x2 by low pass filter B, passband is 0--PBs, P<1, The low-frequency time-domain signal x2L of signal is obtained with a width of PBs；Again by x2 by high-pass filter, passband is PBs-Bs, is obtained The high frequency time-domain signal x2H of signal is with a width of (1-P) Bs；

4th step, is added up using time domain, i.e. the quadratic sum of the mould of time-domain signal, obtains the energy value EL of signal x2L, and signal The energy value EH of x2H；

5th step, tries to achieve ratio R=EL/EH；

6th step, thresholding are demarcated, and the data to having signal and no signal are repeatedly sought R values first, are obtained by statistical probability Thresholding C1 and C2, C2>The size of C1, C2 value mainly affects the size of false dismissal probability, C1 mainly to affect false alarm probability, selected Thresholding should ensure that the unfavorable factor of both the above is possible little；

7th step, the renewal of flag bit flag, flag=0 represent that a front testing result is no signal, it is this kind of under the conditions of, only Have and work as R>It is judged to currently detected signal during C2, flag is changed into 1；Work as flag=1, represent a front testing result to there is letter Number, it is this kind of under the conditions of, only work as R<It is judged to currently be not detected by signal during C1, flag is changed into 0；

According to flag bit, 8th step, controls whether subsequent demodulation thread etc. is opened：Flag=1, opens subsequent demodulation thread etc., no Subsequent demodulation thread is closed then.