CN116634558A - UWB CIR-based target dynamic and static state judgment method - Google Patents
UWB CIR-based target dynamic and static state judgment method Download PDFInfo
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Abstract
The invention discloses a target dynamic and static state judging method based on UWB CIR, which comprises the following steps: 1) Calculating a detection threshold C th The method comprises the steps of carrying out a first treatment on the surface of the 2) Obtaining a front edge point of the head diameter; 3) Obtaining all effective extreme points; 4) Determining a head diameter vertex and a strongest diameter vertex; 5) Calculating the first path energy, the strongest path energy and the received signal energy; 6) Obtaining the local sequence s loc The method comprises the steps of carrying out a first treatment on the surface of the 7) Obtaining the maximum correlation coefficient r coef The method comprises the steps of carrying out a first treatment on the surface of the 8) Obtaining the first diameter energy change delta P FP Maximum diameter energy variation Δp MP And a received signal energy change Δp Rx The method comprises the steps of carrying out a first treatment on the surface of the 9) And outputting the dynamic and static states of the measurement target. The invention adopts the target dynamic and static state judging method based on UWB CIR with the structure, and only needs to measure two adjacent timesThe channel impulse response of the quantity is analyzed, excessive historical data is not required to be stored, and the complexity of the system is reduced; the dynamic and static states of the measurement target can be accurately judged by extracting a plurality of pieces of effective information for comprehensive analysis, effective input is provided for positioning, positioning strategies are selected by a positioning algorithm according to the dynamic and static states of the target, and positioning accuracy and system stability are improved.
Description
Technical Field
The invention relates to the technical field of target dynamic and static state judgment, in particular to a target dynamic and static state judgment method based on UWB CIR.
Background
At present, an outdoor positioning technology based on GNSS is relatively mature, but in the indoor, satellite signals are easily shielded, normal positioning service cannot be completed, and positioning accuracy cannot meet service requirements. In recent years, the demand for high-precision positioning services is increasing, and 70% -80% of activities of people are counted to occur indoors, so that the indoor positioning technology is of great significance. Based on various requirements, many corresponding positioning technologies have been developed and achieve good results, such as infrared, radio frequency identification, ultrasound, WIFI, bluetooth, zigbee, visual positioning, and the like. However, the positioning system has the defects of low positioning precision or severe requirements on the environment, and cannot meet the requirements of people on high precision and good environment self-adaption of the indoor positioning sensing system.
Compared with other wireless positioning technologies, the UWB has the advantages of strong anti-interference capability, extremely wide bandwidth, high transmission rate, small power consumption and the like. In the positioning process based on the ranging result, the robustness of the positioning result is often provided by using methods such as Kalman filtering, etc., but when the motion state of the target is suddenly changed, the positioning result is delayed relative to the actual position due to the influence of the filter. To reduce this effect, it is necessary to identify the motion state of the object to dynamically adjust the use of the filter. Therefore, the judgment of the dynamic and static states of the target has important significance for improving the real-time performance of the positioning result, and is also an important point of current research.
Disclosure of Invention
The invention aims to provide a target dynamic and static state judging method based on UWB CIR, which is used for solving the problem that a positioning result is lagged relative to an actual position due to abrupt change of a target motion state and use of a filter in a positioning process based on a ranging result.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a target dynamic and static state judging method based on UWB CIR comprises the following steps:
step 1, calculating a detection threshold C according to a channel impulse response sequence output by a chip th ：
Wherein C (i) is the value of the channel impulse response sequence corresponding to index value i, abs () is the absolute value operation, N noi The noise length used for calculating the detection threshold, R th Adjusting the coefficient for the detection threshold;
step 2, using detection threshold C th Comparing the first path with each data value in the channel impulse response sequence to obtain a leading edge point of the first path, wherein the specific comparison method comprises the following steps: when abs (C (i) edge ) First satisfies abs (C (i) edge ))>C th And abs (C (i) edge ))＜abs(C(i edge +1)), then C (i) edge ) I is the leading edge point edge Index value for leading edge point;
and 3, extracting extreme points of the channel impulse response sequence by taking the front edge point as a starting point, and comparing the extracted extreme points with a detection threshold value to obtain all effective extreme points, wherein the specific method comprises the following steps of:
1) Firstly, taking a front edge point as a starting point, and extracting extreme points of a channel impulse response sequence:
with the current point abs (C (i n ) With two adjacent points abs (C (i) n -1)) and abs (C (i) n +1)) if abs (C (i) n ))>abs(C(i n -1)) and abs (C (i) n ))>abs(C(i n +1)), abs (C (i) n ) Is an extreme point;
2) Using the extreme point extracted in 1) and the detection threshold C th Comparing to obtain all effective extreme points: if abs (C (i) n ))>C th Abs (C (i) n ) Is an effective extreme point;
step 4, determining a head diameter vertex and a strongest diameter vertex: will be the first one withThe effective extreme points are denoted as head-path vertices, abs (C (i 1 ) And detecting the maximum value of all the effective extreme points to obtain the maximum effective extreme point and marking the maximum effective extreme point as the maximum diameter vertex, namely abs (C (i) MP ))；
Step 5, calculating the first path energy, the strongest path energy and the received signal energy:
1) The head diameter energy P is calculated by the following formula FP ：
Wherein abs (C (i) 1 ) The amplitude of the peak of the first diameter in the step 4, R cvt To quantify the conversion relationship of number to voltage, abs (C (i 1 ))*R cvt Is the voltage value at the peak of the first path, R is the resistance value, (abs (C (i) 1 ))*R cvt ) 2 R is the power value of the head diameter peak,power value of head diameter vertex in dBm, A dB The amplification factor of the analog front end;
2) The strongest path energy P is calculated using the following formula MP ：
Wherein abs (C (i) MP ) The amplitude of the peak of the strongest diameter in the step 4, R cvt To quantify the conversion relationship of number to voltage, abs (C (i MP ))*R cvt The voltage value at the peak of the strongest path, R, is the resistance value (abs (C (i) MP ))*R cvt ) 2 R is the power value of the top point of the strongest path,the power value of the strongest path peak in dBm, A dB The amplification factor of the analog front end;
3) The joint is calculated using the following formulaReceived signal energy P RX ：
Wherein Np is the total number of all effective extreme points, R cvt To quantify the conversion relationship of number to voltage, abs (C (i n ))*R cvt Is the voltage value of the nth effective extreme point, R is the resistance value (abs (C (i) n ))*R cvt ) 2 R is the power value of the nth effective extreme point,power value of nth effective extreme point in dBm, A dB The amplification factor of the analog front end;
step 6, obtaining the local sequence s loc The specific method comprises the following steps: taking the index value of the front edge point as a starting point and the index value of the last effective extreme point as an end point, extracting a channel impulse response sequence and normalizing, wherein the specific algorithm is as follows:
wherein i is Np For the index value corresponding to the last effective extreme point, conj () is conjugate operation, abs (C (i)) is the absolute value of the channel impulse response sequence corresponding to index value i;
step 7, performing convolution operation on the local sequence calculated last time and the channel impulse response sequence output by the chip to obtain a convolved correlation coefficient, and performing maximum value detection according to all convolution operation results to obtain a maximum correlation coefficient r coef ：
Wherein, max () is maximum value operation, S' loc For the last calculated local sequence, N loc For the length of the local sequence, abs (C (τ)) represents the absolute value of the channel impulse response sequence with index value τ, S' loc (τ -i+1) represents the value of the local sequence with index value τ -i+1 corresponding to the last calculation;
step 8, using the current measured first path energy, the strongest path energy and the received signal energy to make difference with the last measured first path energy, strongest path energy and received signal energy to obtain a first path energy change delta P Fp Maximum diameter energy variation Δp MP And a received signal energy change Δp Rx ；
Step 9, executing logic judgment and outputting the dynamic and static states of the measurement target:
first, the energy difference DeltaP between the current measured first path energy and the current measured received signal energy is calculated Rx-FP The calculation method is as follows:
ΔP Rx-FP ＝abs(P Rx -P FP )
secondly, calculating the energy difference delta P 'between the energy of the first path measured last time and the energy of the received signal measured last time' Rx-FP The calculation method is as follows:
ΔP′ Rx-FP ＝abs(P′ Rx -P′ FP )
when the condition (P) FP ＝P MP )&&(P′ FP ＝P′ MP ) Or satisfy DeltaP Rx-FP >ΔP th &&ΔP′ Rx-FP >ΔP th At this time, the characteristics of the channel impulse response sequence are not obvious, and the dynamic and static states of the target cannot be judged;
when the condition (DeltaP) FP ＜ΔP FPth )&&(ΔP MP ＜ΔP MPth )&&(ΔP Rx ＜ΔP Rxth )&&(r coef >r th ) At the moment, the similarity of the channel impulse response sequences measured twice is extremely high, and the target is judged to be in a static state;
if the two conditions are not met, judging that the target is in a motion state;
wherein P is FP For the current measurement of the first path energy, P MP For currently measuring the strongest pathEnergy, P Rx For the current measurement of the received signal energy, P' FP For last measurement of head-diameter energy, P' MP For last measurement of strongest path energy, P' Rx For last measurement of received signal energy r coef For maximum correlation coefficient, ΔP FP ΔP, the change of the head diameter energy MP ΔP for the strongest path energy variation Rx To receive signal energy variations ΔP th For the threshold value of the difference between the current measurement head path peak energy and the current measurement received signal energy, deltaP FPth Measuring a threshold value of the first path energy difference for two adjacent times; ΔP MPth Measuring a threshold value of the strongest path energy difference for two adjacent times; ΔP Rxth A threshold value for measuring the received signal energy difference for two adjacent times; r is (r) th Is the threshold for the maximum correlation coefficient.
Preferably, in step 1, N noi The noise length used for calculating the detection threshold is the first half or the fourth or the eighth of the channel impulse response sequence, R th The detection threshold adjustment coefficient is 6.
Preferably, in step 8,
ΔP FP ＝abs(P FP -P′ FP )
P FP for the current measurement of the head diameter vertex energy, P' FP Measuring the head diameter vertex energy for the last time;
ΔP MP ＝abs(P MP -P′ MP )
P MP for the current measurement of the strongest path vertex energy, P' MP Measuring the maximum diameter vertex energy for the last time;
ΔP Rx ＝abs(P Rx -P′ Rx )
P Rx for the current measurement of the received signal energy, P' Rx The received signal strength is measured for the last time.
Preferably, in step 9, the threshold Δp of the difference between the current measured first path energy and the current measured received signal energy is calculated th For 8dB, the threshold value delta P of the energy difference of the first path is measured twice adjacently FPth 6dB; threshold deltap of the strongest path energy difference measured in two adjacent times MPth 6dB; adjacent twoSub-measurement of the threshold Δp of the received signal energy difference Rxth 6dB; threshold r of maximum correlation coefficient th 0.8.
Preferably, in step 5, the resistance R is 50 ohms and the amplification factor A of the analog front end dB Is between 0 and 60 dB.
The target dynamic and static state judging method based on UWB CIR adopting the structure has the following beneficial effects:
1. the novel target dynamic and static state judging method is provided, so that the application scene of UWB is enriched and the UWB function is expanded;
2. according to the method, only channel impulse responses measured in two adjacent times are needed to be analyzed, excessive historical data are not needed to be stored, and the complexity of a system is reduced;
3. and 9, extracting a plurality of effective information for comprehensive analysis, so that the dynamic and static states of the measured target can be accurately judged, effective input is provided for positioning, a proper positioning strategy is selected by a positioning algorithm according to the dynamic and static states of the target, and the positioning accuracy and the system stability are improved.
Drawings
FIG. 1 is a flow chart of a target dynamic and static state judging method based on UWB CIR;
FIG. 2 is a schematic diagram of a channel impulse response sequence in a target dynamic and static state judgment method based on UWB CIR according to the invention;
FIG. 3 is a schematic diagram of local sequence extraction in the UWB CIR-based target dynamic and static state judgment method of the invention;
fig. 4 is a schematic diagram of calculating a correlation coefficient according to a local sequence and a channel impulse response sequence in the target dynamic and static state judging method based on UWB CIR according to the present invention.
Detailed Description
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
A target dynamic and static state judging method based on UWB CIR comprises the following steps:
step 1, calculating a detection threshold C according to a channel impulse response sequence output by a chip th ：
Wherein C (i) is the value of the channel impulse response sequence corresponding to index value i, abs () is the absolute value operation, N noi The noise length used for calculating the detection threshold, R th The coefficients are adjusted for the detection threshold. N (N) noi The noise length used for calculating the detection threshold is the first half or the fourth or the eighth of the channel impulse response sequence, R th The detection threshold adjustment coefficient is 6, so that the situation of false detection and missing detection can be well balanced.
Step 2, using detection threshold C th Comparing the first path with each data value in the channel impulse response sequence to obtain a leading edge point of the first path, wherein the specific comparison method comprises the following steps: when abs (C (i) edge ) First satisfies abs (C (i) edge ))>C th And abs (C (i) edge ))＜abs(C(i edge +1)), then C (i) edge ) I is the leading edge point edge Is the index value of the leading edge point.
And 3, extracting extreme points of the channel impulse response sequence by taking the front edge point as a starting point, and comparing the extracted extreme points with a detection threshold value to obtain all effective extreme points. The specific method comprises the following steps:
1) Firstly, taking a front edge point as a starting point, and extracting extreme points of a channel impulse response sequence:
with the current point abs (C (i n ) With two adjacent points abs (C (i) n -1)) and abs (C (i) n +1)) if abs (C (i) n ))>abs(C(i n -1)) and abs (C (i) n ))>abs(C(i n +1)), abs (C (i) n ) Is an extreme point;
2) Using the extreme point extracted in 1) and the detection threshold C th Comparing to obtain all effective extreme points: if abs (C (i) n ))>C th Abs (C (i) n ) Is the effective extreme point. As shown in fig. 2, all the effective extremum points are written in turn as: abs (C (i) 1 ))、…、abs(C(i n-1 ))、abs(C(i n ))。
Step 4, determining a head diameter vertex and a strongest diameter vertex: the first effective extreme point is noted as the head-path vertex, abs (C (i 1 ) And detecting the maximum value of all the effective extreme points to obtain the maximum effective extreme point and marking the maximum effective extreme point as the maximum diameter vertex, namely abs (C (i) MP ))；
Step 5, calculating the first path energy, the strongest path energy and the received signal energy:
1) The head diameter energy P is calculated by the following formula FP ：
Wherein abs (C (i) 1 ) The amplitude of the peak of the first diameter in the step 4, R cvt To quantify the conversion relationship of number to voltage, abs (C (i 1 ))*R cvt The quantized number of the first-path vertex is converted into a voltage value, R is a resistance value, (abs (C (i) 1 ))*R cvt ) 2 R is the power value of the head diameter peak,the unit of the power value of the calculated head path peak can be converted into dBm, A dB Is the amplification of the analog front end. Conversion relation of quantized number and voltage->AADC is ADC peak value, D ADC For the quantization number corresponding to the peak value of the ADC, N ACC To obtain the total accumulated number of channel impulse response sequences. The resistance value R is 50 ohm, and the amplification factor A of the analog front end dB Is between 0 and 60 dB.
2) The strongest path energy P is calculated using the following formula MP ：
Wherein abs (C (i) MP ) Is) isThe amplitude of the top point of the strongest diameter in the step 4, R cvt To quantify the conversion relationship of number to voltage, abs (C (i MP ))*R cvt The voltage value at the peak of the strongest path, R, is the resistance value (abs (C (i) MP ))*R cvt ) 2 R is the power value of the top point of the strongest path,the power value of the strongest path peak in dBm, A dB Is the amplification of the analog front end. Conversion relation of quantized number and voltage-> A ADC For ADC peak value, D ADC For the quantization number corresponding to the peak value of the ADC, N ACC To obtain the total accumulated number of channel impulse response sequences. The resistance value R is 50 ohm, and the amplification factor A of the analog front end dB Is between 0 and 60 dB.
3) The received signal energy P is calculated using the following formula RX ：
Wherein Np is the total number of all effective extreme points, R cvt To quantify the conversion relationship of number to voltage, abs (C (i n ))*R cvt Is the voltage value of the nth effective extreme point, R is the resistance value (abs (C (i) n ))*R cvt ) 2 R is the power value of the nth effective extreme point,power value of nth effective extreme point in dBm, A dB Is the amplification of the analog front end. Conversion relation of quantized number and voltage->A ADC For ADC peak value, D ADC For the quantization number corresponding to the peak value of the ADC, N ACC To obtain the total accumulated number of channel impulse response sequences. The resistance value R is 50 ohm, and the amplification factor A of the analog front end dB Is between 0 and 60 dB.
Step 6, obtaining the local sequence s loc The specific method comprises the following steps: referring to fig. 3, taking the index value of the leading edge point as a starting point and the index value of the last effective extremum point as an end point, extracting and normalizing the channel impulse response sequence, wherein the specific algorithm is as follows:
wherein i is Np For the index value corresponding to the last effective extreme point, conj () is conjugate operation, abs (C (i)) is the absolute value of the channel impulse response sequence corresponding to index value i;
step 7, performing convolution operation on the local sequence calculated last time and the channel impulse response sequence output by the chip to obtain a convolved correlation coefficient shown in fig. 4, and performing maximum value detection according to all convolution operation results to obtain a maximum correlation coefficient r coef ：
Wherein, max () is maximum value operation, S' loc For the last calculated local sequence, N loc For the length of the local sequence, abs (C (τ)) represents the absolute value of the channel impulse response sequence with index value τ, S' loc (τ -i+1) represents the value of the local sequence with index value τ -i+1 corresponding to the last calculation;
step 8, using the current measured first path energy, the strongest path energy and the received signal energy to make difference with the last measured first path energy, strongest path energy and received signal energy to obtain a first path energy change delta P FP Maximum diameter energy variation Δp MP And a received signal energy change Δp Rx ：
ΔP FP ＝abs(P FP -P′ FP )
P FP For the current measurement of the head diameter vertex energy, P' FP Measuring the head diameter vertex energy for the last time;
ΔP MP ＝abs(P MP -P′ MP )
P MP for the current measurement of the strongest path vertex energy, P' MP Measuring the maximum diameter vertex energy for the last time;
ΔP Rx ＝abs(P Rx -P′ Rx )
P Rx for the current measurement of the received signal energy, P' Rx The received signal strength is measured for the last time.
Step 9, executing logic judgment and outputting the dynamic and static states of the measurement target:
first, the energy difference DeltaP between the current measured first path energy and the current measured received signal energy is calculated Rx-FP The calculation method is as follows:
ΔP Rx-FP ＝abs(P Rx -P FP )
secondly, calculating the energy difference delta P 'between the energy of the first path measured last time and the energy of the received signal measured last time' Rx-FP The calculation method is as follows:
ΔP′ Rx-FP ＝abs(P′ Rx -P′ FP )
when the condition (P) FP ＝P MP )&&(P′ FP ＝P′ MP ) Or satisfy DeltaP Rx-FP >ΔP th &&ΔP′ Rx-FP >ΔP th At this time, the characteristics of the channel impulse response sequence are not obvious, and the dynamic and static states of the target cannot be judged;
when the condition (DeltaP) FP ＜ΔP FPth )&&(ΔP MP ＜ΔP MPth )&&(ΔP Rx ＜ΔP Rxth )&&(r coef >r th ) At the moment, the similarity of the channel impulse response sequences measured twice is extremely high, and the target is judged to be in a static state;
if the two conditions are not met, judging that the target is in a motion state;
wherein P is FP For the current measurement of the first path energy, P MP For the current measurement of the strongest path energy, P Rx For the current measurement of the received signal energy, P' FP For last measurement of head-diameter energy, P' MP For last measurement of strongest path energy, P' Rx For last measurement of received signal energy r coef For maximum correlation coefficient, ΔP FP ΔP, the change of the head diameter energy MP ΔP for the strongest path energy variation Rx To receive signal energy variations ΔP th For the threshold value of the difference between the current measurement head path peak energy and the current measurement received signal energy, deltaP FPth Measuring a threshold value of the first path energy difference for two adjacent times; ΔP MPth Measuring a threshold value of the strongest path energy difference for two adjacent times; ΔP Rxth A threshold value for measuring the received signal energy difference for two adjacent times; r is (r) th Is the threshold for the maximum correlation coefficient.
Threshold deltaP of difference between current measurement first path energy and current measurement received signal energy th For 8dB, the threshold value delta P of the energy difference of the first path is measured twice adjacently FPth 6dB; threshold deltap of the strongest path energy difference measured in two adjacent times MPth 6dB; threshold deltap of received signal energy difference measured in two adjacent times Rxth 6dB; threshold r of maximum correlation coefficient th 0.8.
Therefore, the method for judging the dynamic and static states of the target based on the UWB CIR only needs to analyze the channel impulse response measured twice adjacently, does not need to store excessive historical data, and reduces the complexity of the system; the dynamic and static states of the measurement target can be accurately judged by extracting a plurality of pieces of effective information for comprehensive analysis, effective input is provided for positioning, a proper positioning strategy is selected by a positioning algorithm according to the dynamic and static states of the target, and the positioning accuracy and the system stability are improved.
The foregoing is a specific embodiment of the present invention, but the scope of the present invention should not be limited thereto. Any changes or substitutions that would be obvious to one skilled in the art are deemed to be within the scope of the present invention, and the scope is defined by the appended claims.
Claims (5)
1. A target dynamic and static state judging method based on UWB CIR is characterized in that: the method comprises the following steps:
step 1, calculating a detection threshold C according to a channel impulse response sequence output by a chip th ：
Wherein C (i) is the value of the channel impulse response sequence corresponding to index value i, abs () is the absolute value operation, N noi The noise length used for calculating the detection threshold, R th Adjusting the coefficient for the detection threshold;
step 2, using detection threshold C th Comparing the first path with each data value in the channel impulse response sequence to obtain a leading edge point of the first path, wherein the specific comparison method comprises the following steps: when abs (C (i) edge ) First satisfies abs (C (i) edge ))>C th And abs (C (i) edge ))<abs(C(i edge +1)), then C (i) edge ) I is the leading edge point edge Index value for leading edge point;
and 3, extracting extreme points of the channel impulse response sequence by taking the front edge point as a starting point, and comparing the extracted extreme points with a detection threshold value to obtain all effective extreme points, wherein the specific method comprises the following steps of:
1) Firstly, taking a front edge point as a starting point, and extracting extreme points of a channel impulse response sequence:
with the current point abs (C (i n ) With two adjacent points abs (C (i) n -1)) and abs (C (i) n +1)) if abs (C (i) n ))>abs(C(i n -1)) and abs (C (i) n ))>abs(C(i n +1)), abs (C (i) n ) Is an extreme point;
2) Using the extreme point extracted in 1) and the detection threshold C th Comparing to obtain all effective extreme points: if abs (C (i) n ))>C th Abs (C (i) n ) Is an effective extreme point;
step 4, determining a head diameter vertex and a strongest diameter vertex: the first effective extreme point is noted as the head-path vertex, abs (C (i 1 ) And detecting the maximum value of all the effective extreme points to obtain the maximum effective extreme point and marking the maximum effective extreme point as the maximum diameter vertex, namely abs (C (i) MP ))；
Step 5, calculating the first path energy, the strongest path energy and the received signal energy:
1) The head diameter energy P is calculated by the following formula FP ：
Wherein abs (C (i) 1 ) The amplitude of the peak of the first diameter in the step 4, R cvt To quantify the conversion relationship of number to voltage, abs (C (i 1 ))*R cvt Is the voltage value at the peak of the first path, R is the resistance value, (abs (C (i) 1 ))*R cvt ) 2 R is the power value of the head diameter peak,power value of head diameter vertex in dBm, A dB The amplification factor of the analog front end;
2) The strongest path energy P is calculated using the following formula MP ：
Wherein abs (C (i) MP ) The amplitude of the peak of the strongest diameter in the step 4, R cvt To quantify the conversion relationship of number to voltage, abs (C (i MP ))*R cvt The voltage value at the peak of the strongest path, R, is the resistance value (abs (C (i) MP ))*R cvt ) 2 R is the power value of the top point of the strongest path,the power value of the strongest path peak in dBm, A dB The amplification factor of the analog front end;
3) The received signal energy P is calculated using the following formula RX ：
Wherein Np is the total number of all effective extreme points, R cvt To quantify the conversion relationship of number to voltage, abs (C (i n ))*R cvt Is the voltage value of the nth effective extreme point, R is the resistance value (abs (C (i) n ))*R cvt ) 2 R is the power value of the nth effective extreme point,power value of nth effective extreme point in dBm, A dB The amplification factor of the analog front end;
step 6, obtaining the local sequence s loc The specific method comprises the following steps: taking the index value of the front edge point as a starting point and the index value of the last effective extreme point as an end point, extracting a channel impulse response sequence and normalizing, wherein the specific algorithm is as follows:
wherein i is Np For the index value corresponding to the last effective extreme point, conj () is conjugate operation, abs (C (i)) is the absolute value of the channel impulse response sequence corresponding to index value i;
step 7, performing convolution operation on the local sequence calculated last time and the channel impulse response sequence output by the chip to obtain a convolved correlation coefficient, and performing maximum value detection according to all convolution operation results to obtain a maximum correlation coefficient r coef ：
Wherein, max () is maximum value operation, S' loc For the last calculated local sequence, N loc For the length of the local sequence, abs (C (τ)) represents the absolute value of the channel impulse response sequence with index value τ, S' loc (τ -i+1) represents the value of the local sequence with index value τ -i+1 corresponding to the last calculation;
step 8, using the current measured first path energy, the strongest path energy and the received signal energy to make difference with the last measured first path energy, strongest path energy and received signal energy to obtain a first path energy change delta P FP Maximum diameter energy variation Δp MP And a received signal energy change Δp Rx ；
Step 9, executing logic judgment and outputting the dynamic and static states of the measurement target:
first, the energy difference DeltaP between the current measured first path energy and the current measured received signal energy is calculated Rx-FP The calculation method is as follows:
ΔP Rx-FP ＝abs(P Rx -P FP )
secondly, calculating the energy difference delta P 'between the energy of the first path measured last time and the energy of the received signal measured last time' Rx-FP The calculation method is as follows:
ΔP′ Rx-FP ＝abs(P′ Rx -P′ FP )
when the condition (P) FP ＝P MP )&&(P' FP ＝P' MP ) Or satisfy DeltaP Rx-FP >ΔP th &&ΔP' Rx-FP >ΔP th At this time, the characteristics of the channel impulse response sequence are not obvious, and the dynamic and static states of the target cannot be judged;
when the condition (DeltaP) FP <ΔP FPth )&&(ΔP MP <ΔP MPth )&&(ΔP Rx <ΔP Rxth )&&(r coef >r th ) At this time, the first and second electrodes are connected,the similarity of the channel impulse response sequences measured twice is extremely high, and the target is judged to be in a static state;
if the two conditions are not met, judging that the target is in a motion state;
wherein P is FP For the current measurement of the first path energy, P MP For the current measurement of the strongest path energy, P Rx For the current measurement of the received signal energy, P' FP For last measurement of head-diameter energy, P' MP For last measurement of strongest path energy, P' Rx For last measurement of received signal energy r coef For maximum correlation coefficient, ΔP FP ΔP, the change of the head diameter energy MP ΔP for the strongest path energy variation Rx To receive signal energy variations ΔP th For the threshold value of the difference between the current measurement head path peak energy and the current measurement received signal energy, deltaP FPth Measuring a threshold value of the first path energy difference for two adjacent times; ΔP MPth Measuring a threshold value of the strongest path energy difference for two adjacent times; ΔP Rxth A threshold value for measuring the received signal energy difference for two adjacent times; r is (r) th Is the threshold for the maximum correlation coefficient.
2. The method for determining the dynamic and static states of the target based on the UWB CIR according to claim 1, wherein the method comprises the following steps: in step 1, N noi The noise length used for calculating the detection threshold is the first half or the fourth or the eighth of the channel impulse response sequence, R th The detection threshold adjustment coefficient is 6.
3. The method for determining the dynamic and static states of the target based on the UWB CIR according to claim 2, wherein the method comprises the following steps: in the step 8 of the process, the process is carried out,
ΔP FP ＝abs(P FP -P′ FP )
P FP for the current measurement of the head diameter vertex energy, P' FP Measuring the head diameter vertex energy for the last time;
ΔP MP ＝abs(P MP -P′ MP )
P MP for the current measurement of the strongest path vertex energy, P' MP Measuring the maximum diameter vertex energy for the last time;
ΔP Rx ＝abs(P Rx -P′ Rx )
P Rx for the current measurement of the received signal energy, P' Rx The received signal strength is measured for the last time.
4. The method for determining the dynamic and static states of the target based on the UWB CIR according to claim 3, wherein the method comprises the following steps: in step 9, the threshold Δp of the difference between the current measured first path energy and the current measured received signal energy th For 8dB, the threshold value delta P of the energy difference of the first path is measured twice adjacently FPth 6dB; threshold deltap of the strongest path energy difference measured in two adjacent times MPth 6dB; threshold deltap of received signal energy difference measured in two adjacent times Rxth 6dB; threshold r of maximum correlation coefficient th 0.8.
5. The method for determining the dynamic and static states of the target based on the UWB CIR according to claim 4, wherein the method comprises the following steps: in step 5, the resistance value R is 50 ohms, and the amplification factor A of the analog front end dB Is between 0 and 60 dB.
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